Better, Faster, Cheaper Consumer Insight: Discussions, Challenges and Opportunities of Social and Digital Consumer Intelligence
Discussions, challenges, and opportunities of social intelligence and wider digital consumer intelligence for better, faster, cheaper consumer insight.
Better, Faster, Cheaper Customer Insight
The discussions, challenges, and opportunities of social and digital consumer intelligence.
A Note From Our Editor
The growing need for social and digital consumer intelligence.
Editors Note
The pressure is on to meet shrinking budgets and timescales for consumer insight. Let me introduce where social and digital consumer intelligence can help to meet your insight challenges.
Dr Jillian Ney
Founder
The Social Intelligence Lab
As we enter 2020, change in the customer insights landscape is accelerating at an unrelenting pace with new data sources, technologies, and methodologies continuing to re-shape our industry.
We’re being tasked with finding better, faster and cheaper approaches to consumer insights and never before have there been so many options to choose from.
Recently, there has been a growing acceptance that insights professionals can adopt new, faster methods with reduced accuracy to answer less complex questions. The slew of new research technologies offer promise, but we still have a lack of understanding of what new technologies and approaches are best suited where.
There’s also a growing renaissance of qualitative research and the adoption of 'voice of the customer' data sources. This makes social media intelligence a strong contender for use in future research methodologies. Certainly, the explosion in unstructured data sets from ‘conversational’ data sources (chatbots, voice, branded communities) means that the professionals with skills in interpreting social media data will be in high demand.
The social media intelligence industry itself has moved into a new phase of maturity and integrating with the demand for tech-enabled consumer intelligence - what is being termed digital consumer intelligence.
Digital consumer intelligence is about blending data sources and approaches to create ‘thick data’ in order to more deeply understand the motivations of behavior. It’s about knowing what methodology to implement for accuracy, time and budget.
This collection of discussions, trends, and predictions feature some of The Social Intelligence Lab’s leading experts, forward-thinking clients and trusted vendors across our ecosystem. Together they explore the dynamics and challenges of social and digital consumer intelligence in consumer insights.
We look forward to working together with our clients and partners to better understand the changing landscape, and help insights teams leverage digital consumer intelligence in 2020 and beyond.
I personally hope you find this guide useful as you plan your year ahead.
Dr Jillian Ney
The Social Intelligence Lab
The Social Intelligence Lab
The Social Intelligence Lab is a professional membership community for people running social intelligence programs at the world's leading brands and agencies.
We connect, educate and support our members to help them build stronger insights initiatives through language and conversational data, and other digital consumer intelligence sources.
Together, we challenge industry norms, discuss best practices, and are working to develop ethical standards.
Contents
What you'll discover in this report.
Welcome to better, faster, cheaper customer insight: the discussions, challenges, and opportunities of social and digital consumer intelligence. After a brief introduction, you'll find articles and discussions in four key areas.
Navigating Social and Digital Consumer Intelligence: Tools, Data and Finding What's Important
5. Maturing Into Digital Consumer Intelligence: An interview with Brandwatch Chief Product Officer, Bex Carson, on the ways digital consumer intelligence can help businesses thrive.
6. The Social Market Research Renaissance: Audiense explores the need to differentiate the source of data for effective and actionable customer insights.
7. Navigating the Too Much Information Age: It's not just about more data, but about being able to effectively judge what is important.
Advice from Ipsos for navigating the too much information age.
Handling Language Data: Different Approaches to Analysing Unstructured Data
8. The Future of Insight is From Langage Data: Converseon explores the value of language data and they share ten ways you can easily leverage unstructured data with advanced machine learning.
9. Free Diving in Social Data: Listen+Learn Research believes that to really understand the human experience you need to close the dashboard, roll your sleeves up, and get reading.
New Methods and Use Cases: Innovative Thinking to Make Social and Digital Consumer Intelligence Useful
10. Closing the Gap in Market Research with Social Media Intelligence: Three simple and effective use cases for social media intelligence in marketing from the social intelligence agency, Storyful.
11. Agile Customer Feedback and the Power of Passion Point Audiences: Qutee Social Asking, an effective and unique approach to fast insights from online audiences, focus group creation and report creation.
12. Expert Predictions: Predictions on integrating digital consumer intelligence into customer insights from independent experts.
Other Things You Might Need
13: Getting Started: Where The Social Intelligence Lab can help you reach your social and digital consumer insight challenges.
14: People and Companies: Details on the people and companies featured in this guide.
15: Blurb at the Back: Disclaimers and other things that you might need.
Introduction
We're in the age of tech-enabled
consumer intelligence.
Dr Jillian Ney
Founder
The Social Intelligence Lab
Forward-looking companies are turning customer insight into a source of competitive advantage, and these insight-driven organizations are known to out-perform their peers. However, today’s fast-paced environment means that organizations face rapid change in both technology and consumer behavior, and this is fundamentally changing the nature of customer insights.
Being able to simply search online to get answers to questions has changed expectations in the business world. Easy access to new information and knowledge has increased the desire to get insights immediately. There are more apps that generate large streams of data from online behavior patterns, social media, user reviews, geolocation data, voice search, and more diverse data sources that offer the promise of “instant insight”. New technologies provide the power to process these new data sources but they are not always straightforward to use, and other tech-enabled customer intelligence solutions allow us to research consumers in ways never before possible.
We’re in the age of tech-enabled consumer intelligence – or digital consumer intelligence.
We’re moving away from thinking about “market research” to developing “insight engines” which are democratized across the entire enterprise. In fact, Forrester has predicted that tech-enabled consumer intelligence will overtake traditional market, customer, and product research in the coming year. Making the challenge for insight professionals to not only make the right methodological considerations but to also find the right vendor selections.
Digital consumer intelligence solutions offer the ability to:
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Ask respondents questions, which could be seen as a digitized version of more traditional research approaches.
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Passively collect and analyze data generated through online activities, which is a move away from traditional research approaches and requires a new way of working.
The future of consumer insight is in blending both approaches. Historically there has been a healthy skepticism around passive data collection. The initial entry of “social listening” into the insights industry was bumpy, to say the least. For some, the approach produced inconsistent results and was often regarded as over-promising and under-delivering. However, this sector is maturing and is fundamentally part of digital consumer intelligence. Here’s why:
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There has been an explosion in “language” based data sets. These “voice of the customer” sources are at an all-time high, and a prime example of passive data collection via everyday touchpoints and interactions with organizations. This data is vastly rich is insights and competitive advantage yet is still massively underused. When it comes to analyzing langauge data, the approach taken by social intelligence researchers can be adapted and used with these new data sources. Language data is an extension of social media intelligence.
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There is a growing acceptance in the insights world that accuracy can be reduced for speed, particularly in situations involving less complex decisions.
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There is a renewed understanding that social data is not “magical”. The social listening industry has matured to accept that the data could and should be blended with other data and research sources.
We have created this guide: Better, faster, cheaper consumer insight: discussions, challenges and opportunities in digital consumer intelligence to help you explore the changing nature of research and adoption of digital consumer intelligence.
Inside you will meet some of the leading thinkers, vendors, and service providers pushing the boundaries in digital consumer intelligence. It is designed to answer some of your most pressing questions about these new ways of working, and identify new opportunities to get insight better, faster and more cost-effective insight.
Are you considering expanding your use of social and digital consumer intelligence in 2020?
Maturing Into Digital
Consumer Intelligence
An interview with Brandwatch Chief
Product Officer, Bex Carson, on the ways
digital consumer intelligence can help
businesses thrive.
Maturing into Digital Consumer Intelligence
An interview with Brandwatch Chief Product Officer, Bex Carson, on the ways digital consumer intelligence can help businesses thrive.
Sabrina Dorronsoro
Content Production Specialist
Brandwatch
Over the past decade, data has been at the forefront of brands' efforts to differentiate themselves and win over consumers. But questions remain – how do we take control of it? How do we leverage it? How do we continue to innovate with it?
Digital Consumer Intelligence (DCI) will shape customer insight in 2020 – but how?
I sat down with Bex Carson, Chief Product Officer at Brandwatch, to talk through some of the key ways DCI can improve any business.
Part 1: Depth
The central goal of any kind of research is to understand the complexities of the real world. We seek out patterns in order to paint an accurate (but digestible) picture of reality, so that we can predict what might happen next.
The real world is a complicated place, and humans are complex beings. A datapoint will give you one view on the world and the people in it. To give ourselves the best possible chance of understanding the world accurately, we need to gather data from a diverse range of sources, blending methodologies. Traditionally, this has been prohibitively expensive and time-consuming.
But not anymore.
The digital data explosion, combined with innovative new technologies, have given rise to what we call digital consumer intelligence. From unprompted social mentions to search behavior, sales trends, or weather patterns, we have access to a breadth of data that enables any research question to be tackled with rich contextual data in unprecedented ways
Meanwhile, the widespread adoption of mobile devices has made it easier than ever to access real consumers and ask them questions.
All this data can be triangulated at speed, uncovering unique insights.
“This is where, in a cluttered world, you find your edge,” explains Carson. “When we can be playful with data, we open up the door to unknown unknowns. It’s the birthplace of innovation.”
Part 2: Speed
DCI tools can act as a faster means of insight than more traditional methods in some critical ways. Here are our top four:
1. Instant recruitment to survey: With a DCI survey tool (like Qriously) you can gain instant access to billions of people and prompt them to answer your questions. That means less time recruiting people to complete your survey in the first place and more time analyzing answers collected in real-time.
2. Real-time social insights: When thinking about consumer insights, social media is a key part of the conversation. Today, people don’t hesitate to turn to social media when they want to talk about how much they love or hate a given brand.
There is a big (and valuable) real-time element with social that other data sources simply can’t provide. Brandwatch’s DCI platform receives minute-by-minute social media insight faster than any other platform on the planet.
3. Immediate access to historic trends: Key questions researchers will come upon when analyzing a trend are: Is this something new? Has it happened in the past? Is this a cycle that is being repeated?
You can't go back in time and ask a question, but with social data you can look back at years of verbatim posts to see what people thought at different points in time. At Brandwatch, we have an archive of 1.3 trillion posts back to 2010. That means you can look back and say:
"Ok, well this actually peaked three years ago and then died away and seems to be back now. So, what happened? Is it going to die away again? Should I invest? Will it be bigger this time?”
Getting that kind of fast access to historic trends is invaluable for brands looking to contextualize their recent data.
4. Exploration and iteration in research: Traditional research methods only let you go so far. The process is rigid. You create research questions, gather your data, and then you have what you have. You can’t ask more questions or dive a bit deeper without considerable expense and delay.
With social or real-time surveys, going back into the research to dive deeper is easy. It brings in the possibility of exploration and iteration at the analysis stage, making the process much more flexible.
Finding something new, finding something first, or finding something surprising that your competitors haven’t capitalized on comes from exploration and flexibility with data rather than rigidity.
Part 3: Representation
When it comes to anything technology-centric there are a lot of pervasive myths.
Social data and other sources relating to digital consumer intelligence often get flack regarding representativeness. The idea is that you can’t use online sources for robust research because not everyone is online.
The truth is, these methods are actually much more representative than most traditional approaches today.
For starters, the question of online adoption is void. Nearly everyone is online in some form today. With Qriously, we can distribute surveys to anyone with an app on their phone that shows adverts.
We know that there are plenty more people with phones and apps than there are people that sign up to be a part of an online survey panel (otherwise known as professional survey takers).
We’re also becoming much better at inferring demographic data which you can then weight against the population. Sure, the data in its raw form may not be representative, but that's where the methodology comes in.
“Just like with any consumer intelligence or market research methodology, you don't talk to every person that exists in a given demographic or location, you take a sample,” notes Carson.
“Once you’ve collected your data, you weight it against the population and then extrapolate as to how you can expect the rest of the population to behave based on this information.”
How will Brandwatch DCI shape customer insight in 2020?
So, where does Brandwatch fit into this puzzle? In what ways are we planning to embrace and expand on the things we've been talking about here?
1. Investing in our data and intelligence platform: We have a pretty unique blend of products here at Brandwatch. Our platform can handle, process, and quickly retrieve huge volumes of unstructured text data across many languages.
We are leaders in multilingual unstructured text analytics, enabling us to analyse huge volumes of unprompted consumer opinion data.
Our recent acquisition of Qriously now gives us the ability to ask questions, and to combine prompted and unprompted data. We plan to keep going further with all of this through 2020 and beyond by pulling in contextual data and blending this with our own sources.
One of the great things about digital data is that it usually comes with a time and location stamp so we are able to triangulate time and location with a trend in conversation and find out what the patterns we are seeing are having an impact on.
This contextual data links the digital data we are collecting in the real world.
“Our unparalleled access to historic social data, real-time survey, A.I. powered data analysis and our speedy, proprietary data processing and retrieval platform make Brandwatch the only company to emerge from the social listening space that is fit for market research,” explains Carson.
2. Democratizing business intelligence through intuitive analysis products: The other way we are contributing is with our front end products – our actual user interfaces – putting a huge focus on design and baking good methodology into our user experience.
Making an easy user experience allows for more self-serve research, meaning marketers and other executives can ask questions directly of the data rather than always having to go through data analysts or market research agencies.
By closing the gap between insight and action we make it more possible to embed data-driven decisions into your daily experience.
“The risk of setting insights loose inside a large organization is that inconsistent data can proliferate throughout an organization,” notes Carson.
“To allow our customers to benefit from real-time insights but still keep one source of the truth, Consumer Research has uniquely powerful administrative and compliance tools, making it truly fit for enterprise intelligence.”
Our clients are using Consumer Research to automate everyday reporting tasks and spend the time they save asking more challenging questions of their data. The innovations in data analysis that our clients build within Consumer Research give them the competitive edge they need in today’s highly volatile and competitive market.
We believe that the successful companies of the not-too-distant future will be those who have mastered and operationalized digital consumer intelligence within their organizations. And we’re excited to be playing a pivotal role in this transformation.
Bring on the innovation.
The Social Market Research Renaissance
Audiense explores the need to differentiate the source of data for effective and actionable customer insights.
The Social Market Research Renaissance
The need to differentiate the source of data for effective and actionable customer insights.
Javier Buron
CEO
Audiense
At the end of last year, Nate Elliot pointed to the beginning of a social market research renaissance and I totally share that view. Nevertheless, to understand where researchers can go deeper into customer insight with digital consumer intelligence, it is important to differentiate the source of the data.
The convergence between digital and traditional in all aspects of marketing has given way to a more strategic and holistic vision of business activity. This, together with a better understanding and use of the available data, is turning businesses to a paradigm in which data and insights are a fundamental pillar of the development of their activity to become insights-driven companies.
One of the most comprehensive descriptions of types of data and the strategic capabilities of “digital consumer intelligence” is the one provided in the image on the next page by our friend David Boyle.
As well as working out the data types, Boyle also highlights the importance of differentiating between consumer vs customer vs audience:
“Why 'audience' and not 'customers'? Some of the people you design for and need to communicate with may be direct customers, but many others likely appreciate your brand from afar and are better thought of as an audience rather than as customers (...yet).”
Independently of the data source, researchers can go deeper with digital consumer intelligence by:
- Testing more hypothesis to arrive more quickly at the right answer. With the increasing speed of the technologies to gather, classify and visualize the data.
- Connecting platforms to widen the knowledge of an audience. With the wide range of tools out there we can build upon the connections we see forming, helping to go deeper in our understanding.
Someone who really understands how the nature of the insights is source dependent, is Edward James Bass. In October, he shared some of his work with Social and Survey data to highlight his discovery and validate what he calls, vital human insights. That is, learnings about audiences which inform decision making and strategic direction. He says:
“No one ever shared a tweet which clearly outlined their customer journey when buying a holiday, since that is about as likely as a survey containing a range of responses to cover the whole myriad of topics an audience might talk about online. With this in mind, I strongly recommend that when looking to understand a particular aspect of an audience that analysts consider which tool is best for the task.”
Social Data, as a data source, is particularly prolific when trying to understanding the mind of the consumer.
“Social media data is still the most fertile source for quick and valuable insights into the "mind" of the consumer”
At Audiense, we have seen this type of use from hundreds of brands using our platform. Something we have learned is that Twitter data is specifically unique for understanding:
- The interconnected communities of a particular audience or a conversation.
- The affinity towards bands or influencers of these communities.
- The ability to compare this information with any other benchmark.
These insights then need to be correlated with other sources to validate, expand to put them into context.
Michael Brito, who has wide-ranging experience in working with social data to understand audience behavior, refers to specific examples where social intelligence and digital consumer insight fit into customer insights such as persona development, content marketing, influencer marketing, and sponsorships. Taken from his article “3 Reasons Why Audience Intelligence Should be a Priority in 2020”, he puts things into context.
“2019 was filled with buzz about data-driven storytelling. While it’s good that marketers and pundits are thinking more about data, it’s clear that there’s more work to do. Social listening, performance media and web analytics are top of mind but the missing piece is audience. When I refer to audience, I mean studying and analyzing real people–their interests, characteristics and media habits that make them unique. This way of thinking about analytics is the real disruption.”
We only seem to reaffirm that in the coming ‘cookie-less world’, creativity and audience-first marketing are at the heart of the solution. Indeed, Nielsen has always sited Creative as the main reason for why advertising campaigns are successful (47%), way above Targeting (9%) – see image below. Moreover, Forrester’s Rusty Warner predicts that Content will challenge the crown position of Data management and Analytics, when it comes to brand priorities.
In this sense, many companies have fallen into what David Boyle calls “the personalization trap” in his article in The Most Contagious Report 2019:
“Many companies fall into the personalization trap of perfecting tactical optimization at the expense of strategic guidance and they miss out on growth opportunities as a result. But with the right tools, strategic guidance in the form of an Audience Strategy can be easy to achieve. We find that clustering consumers according to needs will quickly get you a long way towards a good Audience Strategy.
An Audience Strategy will answer questions such as: Which customer types can you more deeply engage? What are their needs? Which customer types are you failing to engage? Why? … The best part? These Audience Strategy questions can be easy to answer, with the right tools.”
We believe this change is for the better and allows brands to be truly audience-first, and puts creativity and audience marketing back at the heart of the strategy.
Navigating the Too
Much Information Age
It's not just about more data, but about being
able to effectively judge what is important.
Advice from Ipsos for navigating the too
much information age.
Navigating the Too Much Information Age
It's not just about more data, but about being able to effectively judge what is important.
Tara Beard-Knowland
Head of Social Intelligence Analytics
Ipsos UK
Ipsos has been in business for well over 40 years, and some parts of our organization are even older. As the Information Age, which started with the advent of personal computing, has progressed, so have research and insights.
Over all those years that we have been in business, we have seen many trends and many fads in how clients use data and what methodologies are hot or not. What we see is that we have by no means reached the nexus of the Information Age – we hear from clients and suppliers that there is no shortage of new information to mine.
The problem is that the Information Age is turning into the Too Much Information Age. You would be hard-pressed to find a department in any organization that doesn't deal with data of some kind. If everyone has access to data and can lay claim to creating some useful finding, what is Insight?
We see many clients grappling with these questions, and we see early signs of an important shift: a digital-first approach, with more triangulation of data sets. For those at the forefront of insights, this leads to a desire to know not just more but to be able to effectively judge what is important. It is like a box of chocolates – there's a lot of great stuff in there, but if you don't have the map of what's what, then you can end up just blindly tasting them until you find the kind that suits you.
Digital resources like social and search are fantastic places to start with landscaping an issue or a category. We have worked on many projects over the past year which have started with a digital fact-finding mission that can change the shape of future work.
For example, a comprehensive view of social media impacting the US retail grocery landscape. We explored the landscape using advanced text analytics to depict what is trending in key categories and determine prevalent associations of client and competitor brands. This sets the stage for other work we are doing to understand trends, brand attributes and effective communications in this space.
US Retail Grocery Landscape Map
Indeed, digital methodologies alone can be more than sufficient to create the landscape understanding. What's especially great about social media data for this is that it gives us the real language that people use, without us feeding them our structured view of the way a sector works.
With all of the information now available, we have all become more acutely aware of where information falls short – whether that be more traditional sources such as surveys or newer sources like social media or communities.
Triangulation is a great way to build more robustness into your data sets. We have seen a trend emerging in this for profiling work in particular, whether as segmentation, personas or other audience mapping. With the addition of social media data, search terms, and online audience profiling (e.g. Synthesio Profiler) to more traditional research methods, we can create more complete, real pictures of people,
Case Study: Looking Beyond the Obvious
Our client conducted a segmentation and identified a core target for a new brand launch. The client's brand offering was sleek and well-designed, with communications to match. Subsequently, we conducted audience profiling of that segment, using Synthesio Profiler. Not only did we discover key interests for our client's core target, but we also discovered that the brands that the target had the most affinity to were busy and frenetic: the very opposite of how the client was portraying itself. This is something the original segmentation did not uncover. The client is now reviewing its comms strategy for this target audience.
As more and more clients start to look for what is important, the first question we recommend asking of any data is 'how can this data be useful to my organization?'. With less traditional data sources, such as social media and search data, it is important to take a view with a wide lens. Most categories and sectors can't directly replace existing data sets with these newer sources. Instead, they can often add new insight, for example about the wider issues affecting your questions, or act as an alert system.
To avoid the challenges that the Too Much Information Age poses, we need to think better, rather than bigger and remember that more is not always more useful.
Three smart moves clients should make with digital data in 2020:
Discover: Find out what's out there first. There is so much information, some of it may already exist in your organization.
Prioritize: What do you need to know and where can you get the information from. Like all the best things in life, it sounds simple but can be challenging to do.
Triangulate: Once you know what's important, don't be afraid to pull different threads of data together to create the full picture. We now have more data than ever at our disposal to help close these gaps in our knowledge.
The Future of Insight is From Language Data
Converseon explores the value of language data and they share ten ways you can easily leverage unstructured data with advanced machine learning.
The Future of Insight is From Language Data
Converseon explores the value of language data and they share ten ways you can easily leverage unstructured data with advanced machine learning.
Rob Key
Founder and CEO
Converseon.ai
Organizations are awash in untapped, insight-rich unstructured data. Customer feedback and unprompted opinion through social media, product reviews, long-form survey verbatims, call center transcripts and more are veritable goldmines of insight for those customer-obsessed companies that can effectively harness, filter, process, and understand this massive, messy data set. Computer World magazine forecasts that unstructured information might account for more than 70%–80% of all data in organizations.
Yet organizations today face a conundrum: even as this data set grows exponentially, most brands are processing and using only a small portion of it— Forrester Research says most organizations are processing less than 21% of this unstructured data. And with some good reason: this unprompted “language data” is complex. Implicit meaning, sarcasm, slang context and much more make it challenging to separate the signals from the noise and make the data actionable in a time span needed for competitive advantage.
Today, however, a growing number of organizations are leveraging advanced natural language processing and text analytics solutions powered by artificial intelligence that are proving to be game-changers and allowing these firms to begin to fully leverage the long untapped value of this data set.
But doing so requires a thoughtful and clear methodology and approach that builds on the latest data science, machine learning validation, and processes. While this article focuses largely on social media, the approaches and lessons can also be applied, with some modification, to other unstructured data sources.
What is social media intelligence?
You’ve probably heard the term social intelligence, but there is a big difference between a hype-laden phrase and real business value. With the social media explosion now a decade old, it’s time for marketers to finally extract the value out of social media conversations—that’s social intelligence.
With social intelligence technology, you can identify the conversations that matter to you and classify them into standard or custom categories that allow you to see trends and make better business decisions. “Intelligence” refers not only to the accuracy of the model but also how well the model meets business requirements.
And by combining social intelligence with advanced analytics, researchers and analysts are discovering vast consumer predictive intelligence. Properly utilized and implemented, social intelligence is proving to have strong quantitative value and predictors of business determinants, such as sales, survey-based tracker results, new trends and more.
What can social intelligence models tell us?
Language is highly complex. Most social-based conversations, for example, do not use specific keywords but are instead conveying implicit opinions. A person likely will not say, “I trust x brand,” but instead likely will “use it with my baby at night because my baby sleeps better.”
In the latter, there is no word specific to connoting trust, but most humans will understand it, and now today, with more advanced natural language understanding technology powered by machine learning, algorithms can process and categorize this level of nuance too - “like humans do.”
Social intelligence requires applying these more advanced annotations —data that is added to the original social conversations to help us categorize and aggregate them -- -- powered by more sophisticated and accurate algorithms.
But since we’re dealing with the complexities of human language, these more advanced and accurate NLP algorithms (or “models”) need to be steeped in a framework -- organizing principles that help define specific annotations and how those annotations get applied to specific sectors. What does “trust” mean for example? What are the inputs and drivers of trust? And can you define it in a way where humans agree on it?
Social intelligence requires “intelligent” algorithms - highly precise, and accurate, detailed, able to classify even nuanced concepts and language and grounded in meaningful frameworks that are consistent and effective for use. These new intelligent algorithms are able to classify:
Some standard annotations that social intelligence models produce are:
- Sentiment: Is the conversation positive towards your brand, negative, or neutral? Sentiment models are designed to answer that question correctly.
- Emotion: Certainly, anger and sadness both convey a negative sentiment, but they might warrant different responses to the customers experiencing the Plutchik’s Wheel of Emotions, which is one way of categorizing emotions, while other social scientists have designed alternative models.
- Intensity: The strength of passion behind an opinion can itself be measured. “It had a slightly butter off-note” is not as strong as “That is the worst-tasting $^#% I have ever tasted”.
- Voice of Customer: Only about 10% of social discussion is from actual consumers (the rest being noise from job listings, advertisements and more). VoC models can filter out all that noise to get to actual consumer opinion and a critical first step for building more complex models for product innovation, customer experience, and brand measurement.
- Trust: Brand trust reflects a customer’s expectation that a product or service (and sometimes corporate behavior) reflect the promises of the brand. Trust is a key quality of any relationship where customers make a purchase, yet brand trust sometimes fluctuates significantly over time. Identifying comments that exhibit brand trust can be challenging, as in the example, “I would be reluctant to use a different brand of shampoo on my infant’s hair.”
- Values: Consumers today expect brands to not only build superior products but also help make the world a better place and take action on important “value.” CSR (“corporate social responsibility”_ models can measure how consumers perceive company efforts including in the areas of brand purpose, environment, and related social issues.
- Innovation: In high tech, consumer electronics, and many other industries, a brand’s reputation for innovation is a critical part of the buyer’s decision-making. Finding the right conversations that reflect innovation is also not easy, because people often comment on things that are new, but not all of them are innovative.
Often, however, what really matters are specific insights about your unique business questions, which requires a custom model that captures specific concepts unique to your company. Custom models classify language “like humans do”, and you’ll finally be able to realize the full value of social data:
- Buyer Journey Stages: Each company (and sometimes each product within a company) overlays a buyer journey onto its customer interactions. One company might have a four-step journey and another might have a six-step journey and each one uses different names for its steps.
- Brand Health/Attributes: Do conversations about your brand align with attributes or not, and are those attributes even relevant or in demand in social conversations?
- Customer Intent: Is the customer trying to buy something or looking for customer service? Or something else? Different businesses attract people for different purposes at different times.
- Emerging Trends: Social data is rich in insight into emerging trends and discoveries before they hit mainstream recognition. Machine learning models can be critical to accelerating and improving innovation at brands by finding these new trends first.
How can you use social intelligence models?
Social intelligence can serve a number of use case within your enterprise, including:
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Advocacy: Who is engaging in conversation that “sell” your brand? As with customer experience, it is sometimes valuable to understand the overall numbers by also sometimes important to identify individual influencers.
- Brand Tracking: Trust, innovation, and safety are all common attributes that many companies need to track on an ongoing basis.
- Crisis Management: Communication professionals need to monitor breaking stories that negatively affect brand image.
- Customer Experience (CX): Customer experience is the product of an interaction between an organization and a customer over the duration of their relationship. It can be measured in aggregate across many customers’ testimonials on social media or it can be segmented down to the individual level to support focused retention efforts.
- Customer Service: Support team identify complaints in social media and reach out to resolve them.
- Market Research: Marketers use social media conversation to understand the wants and needs of their market.
- Product Development: Product managers mine social media to determine popular product features and identify needed features.
- Recruiting: Human resources personnel can identify potential employees through social media conversations.
- Reputation Management: Marketers and communications professionals assess the brand image across the social media population.
- Sales Leads: Salespeople use social media to identify potential purchasers for their offerings.
Why measurement matters
It’s often said that you can’t manage what you can’t measure. For many years, the quality of the data processed through social listening platforms has been opaque at best and disappointing-to-unusable for insights at worst.
It has been difficult, if not impossible, for analysts to clearly measure the accuracy of data in their social listening platforms. As a result, the adoption of social intelligence has too often been stunted by a lack of trust in this massive, messy, unstructured dataset. Market research professionals often look at social data with skepticism because of concerns about accuracy. Senior executives naturally hesitate to accept insights and findings without a clear understanding of the true, quantitative nature of the data.
And with good reason. “Accuracy”—how well systems match the consensus of humans—has often been only slightly better than a coin flip. Additionally, many technologies miss many customer opinions, leading to well-deserved hesitation by market research professionals who cannot effectively integrate this data into advanced analytics models, or use the data to report on key trends to senior executives.
There is good news, however. By directly learning from humans, machine learning algorithms are beginning to unlock the full value of this massive, real-time insight resource.
The convergence of AI with Natural Language Processing (NLP) and social Voice-of-Customer (VoC) data is clearly a critically important development for customer-centric organizations. For many leading organizations, it is representing an entirely new generation of insights, including predictive insights, that are helping to transform brand guidance, reputation management, customer care, customer experience, trend discovery, and marketing research more generally.
Free Diving in Social Data
Listen+Learn Research believes that to really understand the human experience you need to close the dashboard, roll your sleeves up, and get reading.
Free Diving in Social Data
To really understand the human experience you need to close the dashboard, roll your sleeves up, and get reading.
Jeremy Hollow
Founder
Listen+Learn Research
We know that social data has the potential to help us better understand people and their lives. After all, it’s millions of people around the world sharing their thoughts, emotions, and experiences, and it’s there, just waiting to be observed. No more surveys or the same twelve people munching away on your sandwiches in a focus group.
It’s data that’s raw, natural, unfiltered. It’s data that can give researchers unique insights that cannot be found anywhere else. Later we share an example of how social data can help reveal to us aspects of life that traditional research simply can’t reach.
Of course, there are still limits to the usual approach to social data. Something which makes finding new insight harder than it needs to be, leaving people frustrated and in danger of walking away from its potential.
The tortoise and the hare
You know the tale of the tortoise and the hare? Well, something similar is happening in how we’re using social data for research. Instead of the tortoise and the hare, or qual vs. quant, it’s more like the Speed Skater vs. the Free Diver.
This is what lies at the heart of the frustration.
Let’s start with the idea that social data is like a huge ocean of human experience, in the middle of winter...
The speed skater
The Speed Skater is where most of the social intelligence / social insight market is right now.
Their data is the ice, the listening tools are the skates and the racetrack, and the analyst is the skater.
As you’d expect, the Skater is all about speed. They’re quick off the blocks, explosive energy pushing them forward. They quickly cover a lot of ground, getting from question to answer in hours if not days. Quick, agile, nimble.
What we get from social data tends to come from the Speed Skaters. They stay in their lane. Their exposure to and interpretation of the human experience comes from dashboards and analytics. It’s clinical, precise. You see what can be counted – those data points that are frozen in time. It’s all very quantitative.
Cracking the ice
But there’s more than one way to enjoy the water.
What we gain from quickly skating over the data shouldn’t blind us to what’s underneath. We shouldn’t always run the same race on the same track – in doing so, we’ll only know what everyone else knows.
Ice rests on the top and is the easiest thing to see, but we’re all aware that most of the ocean lies beneath. There’s a vast body of fascinating data, rich in life, just waiting to be found. It’s dynamic, living, evolving – the sum of millions of human experiences, opinions, and emotions.
This is the domain of the Free Diver. They’re free to go deep into the human experience, to follow different leads, explore different paths, and to immerse themselves in the depths of the human experience.
What lies beneath
For the Free Diver, the data is a vast unexplored ocean, listening tools are the fins and mask and the diver isn’t one person, but a team of specialist social insight researchers.
The Speed Skater sees the track laid out neatly before them (sentiment analysis, statistics on engagement, topic counts).
The Free Diver is more connected to the water and the life below. They’re in deep. They feel what people feel, they hear what people say, they’re sensitive to what people experience. It’s a much deeper level of human touch. It’s emotional and experiential rather than basic analytics.
The Free Diver respects the ocean and their role within it. They know their limits and the nature of the world they’re exploring. They know they need to plan their trip while being open to change and adapt their approach as they go. They frame rather than constrain how they experience and interpret the human experience.
This is where you find new insight.
Case Study
How a leading cancer charity challenged their blind spots – getting beneath the surface of receiving a cancer diagnosis to transform how they deliver services.
The Business Challenge
Our client’s role is to be there for everyone with cancer, right from the moment they’re diagnosed. However, previous research showed they weren't reaching everyone at this critical moment, and they needed to be.
Their goal is to there at the right time, in exactly the right way. But they didn't always know how and trying to find out was incredibly challenging. It was their blind spot but one they needed to address. To do this, they needed a new approach…
Setting the Scene
Why was this such a challenge? Well, some questions just can’t be asked. How can you ask people about this raw, brutal and life-changing moment when it’s happening? How would you start, what would you ask, how could you even find them?
There are a whole host of obstacles in the way of traditional research, but they knew it was too important to shy away from.
So, they wanted to try something new, to crack beneath the surface of this moment. They knew doing so could transform their impact, the way they design, plan and deliver services, communicate and engage with people.
Connecting with audiences through social insight
They came to us to give social insight a go, to find people at that critical moment and hear in their own words how it felt to be diagnosed.
We discovered people, lots of people. We heard about their experiences, feelings, fears and needs at this rawest of times. But we didn’t find them with data analytics, mentions and likes. We didn’t do it using word clouds and sentiment. We did it through a blend of social quant and qual.
We found people sharing their lives with each other and new friends for the journey they were suddenly on. We found an incredible richness in people’s stories that revealed their experiences and what they needed most but so often lacked. Humanity.
We found three insight themes:
i. The emotional depth and intensity: We heard the fears and anxieties and understood why they existed. For example, we got to understand the 'nature of fear'. We heard what people couldn't say in real life, to their friends and families, but could with others 'like them', in the anonymous safety of forums. We found where this was happening and when; that it's active all day, and that it’s at night when the fear and loneliness really hits. And we understood the language of the newly diagnosed, the metaphors and conversational etiquette they used.
ii. The extent of people’s unmet needs: The questions people asked in social showed what they really needed at this time of huge uncertainty and confusion. We heard about the disconnect between well-meaning professionals when they deliver news, and what needs to be better.
iii. The evolving nature of the experience: It's not static or linear. It changes, there is a journey, and different types of people navigating it. We understood the changing nature of needs from diagnosis into treatment and beyond. The emotional highs and lows, challenges and celebrations which revealed the shifting needs and how to address them in a tailored, person-centered way.
New insight, new action
Understand this moment was important to many different parts of or their operations. Workshopping the results brought this to life for people from strategy, service delivery, and online community management, to marketing, comms and digital.
Main outcomes:
i. Communications: This helped them understand how to connect and engage with people at this moment, in the right place with the right message. It showed the importance of their own online community and the need to integrate this with a new Diagnosis campaign. This led to changing the focus of the website – concentrating on those questions people really want to ask.
ii. Information + Support services: The work shaped assets to support each interaction, e.g. information pages online and materials offline. These now contain more personal stories, and content is tailored better to people’s needs and in language suited to the audience and their stage in the cancer journey.
iii. SEO + Community: They knew communities were crucial and its own was an important asset. But social insight showed it wasn't being found by the people who needed it. The research helped their digital teams address this. It also led to content, delivery and structural changes to the community itself. E.g. signposting of information, the language used by moderators (or people handling their call line), the flow of materials and navigation.
Social media has the potential to achieve what all organizations are looking for: to really understand and know how to connect with people. As our client discovered, social is, by its very nature, a vast ocean of human expression, experience and connections. It let them find what truly matters to the people it wants to support. It let them move beyond seeing them as just numbers, data points or trendlines, and recognise them as people needing help.
Closing the Gap in
Market Research with
Social Media Intelligence
Three simple and effective use cases for social
media intelligence in marketing from the social
intelligence agency, Storyful.
Closing the Gap in Market Research with Social Media Intelligence
Three simple and effective use cases for social media intelligence in marketing.
Jeff Perkins
Executive Director, EMEA
Storyful
Market research is the cornerstone of any good marketing execution. The more a marketer understands their target consumer - the logic goes - the more successful a campaign is likely to be. In fact, last year marketers spent an estimated 47 billion on research globally.
Surveys were sent out, focus groups convened, dashboards crunched numbers and trends were extrapolated. All with the singular aim of painting a clearer picture of the consumer. But, when it comes to what people are actually saying and feeling, there's a gap. Every survey limits the possible answers. Focus groups come with bias. Demographics and psychographics aren’t people and lack the nuance necessary to succeed in today’s media environment.
Social media intelligence is one of the only forms of large scale, unbiased research available to modern marketers ‒ and it’s being woefully underutilized. With the proper refinement and context, social media intelligence can inform how a brand should or should not communicate with its customer base. It can protect brands from launching irrelevant or tone-deaf campaigns or help them lean into the prevailing emotional attitudes governing popular sentiment around a given issue or event.
Here are three ways Storyful’s partners use social media intelligence to inform different facets of marketing:
1. Identifying the gap between public and brand perception: Social media analysis can quickly reveal whether a brand’s mission and goals are well-received and understood by an audience. Consumer attitudes are constantly shifting, and social media conversations reflect these changes. A brand releases one bad marketing campaign and social media will forever record the impact.
Social media intelligence can help brands identify and close potential gaps between what it strives to be and how people actually perceive it. From customer testimonials on YouTube, to employee activism on Glassdoor, what people think of a brand is available for analysis. It’s not just on your owned Facebook and Twitter channel either, it’s everywhere.
2. Producing relevant content: Insights from social media can power marketing brainstorm sessions, allowing brands to create content marketing and advertising that consumers don’t just scroll past. Social media users are constantly sharing their perceptions, fears, challenges, and frustrations. Contextualizing and analyzing these conversations enables brands to create content that speaks to consumer needs. By exhibiting a great understanding of their audiences, companies have the opportunity to use social media intelligence to increase brand authority and favourability.
Storyful recently analyzed social media conversations around air travel in the UK. By tracking consumers’ reactions to developments in the airline industry, we were able to uncover the key motivations currently driving online conversations in this space. One major factor: sustainability.
3. Identifying influential conversations: An understanding of the influences pervading a certain industry or shaping consumer perceptions offers marketers the opportunity to identify the most important conversations around a topic and address any misinformation.
Storyful’s network visualization tool Cosmos allows users to make sense of the conversations happening on Twitter and Reddit around a given topic or #hashtag. Marketers using the tool can identify the “influencers” sitting at the center of any given conversation.
That means going beyond follower count and instead identifying who the authentic voices are at the center of relevant online conversations about an industry or consumer need.
By engaging the individuals with the most influential networks in mature conversations (think: telecommunications brands responding maturely and scientifically to claims that 5G can cause cancer), or creating messaging that reaches them, brands can partake in the matters that affect society and their industry.
Agile Customer Feedback
and the Power of Passion
Point Audiences
Qutee Social Asking, an effective and unique
approach to fast insights from online audiences,
focus group creation and report creation.
Agile Customer Feedback and the Power of Passion Point Audiences
Qutee Social Asking, an effective and unique approach to fast insights from online audiences, focus group creation and report creation.
Tim Wilson
CEO
Qutee
What do community management, influencer marketing, and market research have in common?
People.
More specifically, the power to understand the attitudes and behavior of people.
While market research has always sought to uncover what makes people tick, community management and influencer marketing have traditionally been thought of as routes to reach people rather than understand them. But what if the power of “passion-point audiences” could actually supercharge your customer insights efforts?
Sometimes it takes an unconventional approach to find truths about your customers, your customer experiences, your products, and services.
Over the past decade, technology has reshaped market research, making it easier to observe and ask questions of people, although most methods still require expensive and time-consuming respondent recruitment. All the while our marketing colleagues have been steadily building audiences and relationships — audiences and relationships that can be easily leveraged to obtain customer insight faster and cheaper.
There is no doubt that digital consumer intelligence is changing how we approach market research. Two of the most profound changes are a decrease in the time it takes to run research and an increase in the ability to reach new and diverse respondents.
I personally advocate for a new approach of “social asking”. Social asking increases the speed and agility of the insights process, while simultaneously reduces the expense of respondent recruitment by leveraging existing audiences. You can quickly access the voice of audiences who are passionate about your product, category or industry.
Social Asking with Passion Point Audiences
Social asking helps you to leverage the power of audiences to obtain immediate feedback and insight by asking questions to real people. This isn’t social media intelligence, passive data collection or respondent recruitment usually associated with social media. With social asking you have full control over the questions you ask, you lead the research, you create an immersive experience for the respondents, and you can be confident that you’ll be able to obtain the insight you are looking for.
If you have an online audience, CRM database or access to an influencer you can leverage passion point audiences for agile customer insights with social asking. You think of the questions you need to answer, you publish them, and your audience responds. Imagine tapping into hundreds, thousands or even tens of thousands of people motivated and invested enough to provide you immediate industrial-scale feedback.
We haven't reinvented the survey here. Social asking is about:
- Leveraging existing social and influencer audiences.
- Providing a social and friendly experience to conversational research.
- Avoiding the austere approach of traditional surveys.
- Creating super-sized focus groups free of the limitations of Facebook and Twitter.
- Providing real-time comprehensive reporting that overcomes the data-rich insights poor dilemma.
Social asking and passion point audiences are an unconventional approach to customer insights, but they provide insight faster and at a fraction of the cost of traditional research methods.
What About Respondent Sampling?
Social asking relies on the power of social and influencer audiences, so you don’t get to control the research sample, and we get that respondent sampling is important to research. If a sample isn’t chosen carefully and systematically, it might not represent the population and if the sample doesn’t represent the population, then it can’t be generalized beyond the study.
But what about the times when you need quick insights without any fuss? Or those use cases when you need quick insights to challenge assumptions or gain feedback, and you don’t have the time or budget to spend on expensive agencies. What if you can take the most passionate customers and research their experiences? The respondents with the most valuable opinions that will make or break the online reputation of a product?
We strongly believe that these types of passion point audiences fill the void between social listening and the more traditional “coupon collector” panel group audiences. Better still, what if you can run research while building a super-sized focus group that can be leveraged for insights time and again?
Social asking gives you agile and immediate insights, and is a method you’re confident will produce results. A few of our most prolific use cases:
- Product launch feedback.
- Granular feedback on product or customer experience mechanisms.
- On-going customer experience feedback.
- Opinion and perception-based research.
Case Study: Influencers Finding ‘Game Play’ Insights For a New Gaming Product Launch
The gaming industry is extremely competitive. The key issue when launching a new game is to ensure gameplay is strong from the day of release. With so much online conversation around gaming and new releases, it is critical to quickly correct any major issues before popular gamer opinion turns.
The gaming industry is underpinned by gaming influencers, influencers like YouTuber CapgunTom (Tom). With over 1 million YouTuber subscribers, Tom looks to keep his audience engaged and wants to provide more value to his partners and sponsors. This is one of the reasons why Tom uses Qutee, the social asking platform.
Like every other influencer and brand, Tom finds the ability to extract real-time and accurate insights from his discussions across his social channels very challenging and time-consuming. He uses Qutee to build a “passion-point” audience where he can ask questions and collect comments, opinions, perceptions, and ratings from his audience. This helps him to make more compelling content, but also to offer valuable feedback to his partners and sponsors.
So, when Qutee was commissioned to collect agile gameplay insights around the release of a new $10billion franchise game, we knew we could rely on Tom to leverage his passion point audience to get granular insights into the gameplay.
Qutee worked with Tom to run a conversational research engagement to gauge his audiences’ first thoughts and opinions on the title at launch. Over the course of two weeks, CapgunTom collected 1000 detailed paragraph length comments spread over 139 topics and 4000 polls and ratings.
Could Tom have run this research over his other social media channels? Probably not, and certainly not to this depth. It’s important to note that his regular comment length on his other channels is barely beyond a sentence. The Qutee platform is designed to create an immersive experience for audiences, which encourages them to share and engage, not just with Tom, but with each other.
This immersive experience encourages engagement, increases the depth of responses, and increases trust to share opinions in a safe space. There’s a lot of data collected, and our NLP analytics dashboard works hard to auto-generate quantitative and qualitative insight reports from the conversations.
For the launch of this new $10billion franchise game, Qutee was able to leverage Tom’s passion point audiences to quickly identify granular topics that were causing issues with the players. These included:
- Defending.
- Goalkeeper interaction.
- Server speed.
From here, the client requested that we then run subsequent Qutees around the key game mechanic issues and to delve deeper into player sentiment.
In summary, Qutee’s unique combination of the most advanced commenting system, friendly social experience, real-time analysis, and reporting, meant that the client was able to supplement their traditional social listening analysis with additional passion point audience sentiment beyond what any traditional small scale focus group could ever provide.
Expert Predictions
We asked experts where can digital consumer intelligence help insight teams get to better, faster and cheaper insights in 2020?
Here's what they had to say.
The Consumer Psychologist
In the last few years alone, the industry saw a surge in new and emerging insights methodologies developed for a deeper understanding of consumer behavior. Equally, the awareness around and utility of these tools and methods became more widespread than ever amongst us insights professionals, so the bar is higher for quality and relevance of insights.
2020 will be a year of culmination and productivity when brands will maximize experimentation with the variety of intelligence at disposal to become more proficient in the evolving consumer motivations. The global rise in consumers’ desire for more socially responsible and conscious engagement with brands and products will mean that the new methodologies will push us to abandon a “mobile-first” viewpoint for a “human-first” approach on the way to more sustainable brand-consumer relationships.
Nisa Bayindir
Consumer Psychologist
NisaBayindir.com
The Data Supplier
Like any industry, evolution is necessary to drive growth and transformation as anticipated. Social Intelligence is hitting the next stage of its change. Rather than recruiting special forces like individuals, more and more of this work is being addressed via the tools and platforms with smarter ways to surface insights as well as specialized companies and firms who can and will develop the methodologies and frameworks to drive keen insights. As a supplier, we are excited to see these changes happen like evolutionary adaptions happening in front of our eyes.
I firmly believe that this change will happen on the front lines of the data with hearing and addressing customer feedback and product need. Just like how a product flaw in Robinhood's trading algorithm was identified on Reddit via /Wallstreetbets or a bug bounty for the lastest android release, the users of social media will always save the day. The tools are finally getting strong enough to help identify those needles in the haystack and drive down costs versus traditional research methods. I still believe that the perfect solution will be a hybrid of all processes.
Jim Reynolds
Head of Global Alliances
Socialgist
The Insights Consultant
Social consumer intelligence often gets a bad rep. It’s easy to see why – there’s a lot of noise, irrelevant mentions and sense that “only certain types of people” post. Thing is though, social consumer intelligence isn’t bad; it’s how most brands approach it that’s usually the problem.
In 2020, we need to take a smarter, more analytical and more sophisticated approach to social intelligence. The better use cases will see insights teams cutting the data to focus on behavioral statements to see the actions people take; sentiment drivers on specific topic to see what about it is making them excited or mad; analyzing organic conversations of particular target audiences to discover true interests, and expanding our definition of ‘social’ sources and using more of them to get the right data and people.
Behavioral science is becoming critical to marketers. Effectiveness has been declining for years, so we’re (correctly) trying to understand how people actually behave and act, vs. what they say they’ll do. Social intelligence is still nascent and underutilized as a source for true customer insights. As long as you’re cutting and analyzing the data effectively, it may be the biggest untapped data source for your brand on how people behave, talk and what they care about.
Kristian H. Foged
Principal Insights and Analytics Consultant
Independent Consultant
The Data Scientist
Insight teams can effectively use digital consumer intelligence approaches to get better, faster, and cheaper insights in five ways:
1. Use social/digital media for doing desk research, and initial hypothesis formulation. Not very many people in traditional research world take desk research seriously but it is essential for any strategic formulation.
2. Map out consumer voice points and use digital media to gather insights in all digital influenced voice points
3. Inter-link digital media insights with insights gathered via traditional research methods to create next-gen measurement systems
4. Integrating internal data from different business functions with digital media research has a lot of unexplored potentials
5. The democratizing of digital media insights holds a lot of power. But do it with caution- data is powerful but can also be misused.
Preriit Souda
Data Scientist
PSA Consultants
The Association
In 2020 and beyond we will see digital intelligence evolve to play an even more important role in the overall market research strategy of a company or brand.
Digital intelligence is a form of qualitative research but needs to be orchestrated correctly in order to deem actionable results. Currently, it is mainly being used by larger brands with a strong emphasis on vanity metrics. However, there is so much more valuable data that has yet to be explored. As companies of all sizes begin using social media as a customer service channel, for example, this data over time will assist in VOC analytics, along with customer feedback surveys and other forms of research.
Demographics and the way in which marketers use them to personalize the customer experience will morph more into tribal marketing, in my opinion. Segmentation of groups of consumers should be considered in research along with traditional demographics. Specifically, understanding online behavior at a micro level will allow more personalization--which studies show consumers are wanting. When a brand understands Group X identifies well with Group Y on the subject of XYZ, personalization is achievable in a broader sense, allowing for increased ROI.
Kathy Doring
President
Social Media Market Research Association
The IT Strategy Consultant
Better, faster, cheaper? We've been told for years you can't have all three. But maybe the insights equation is changing given the rise of
machine learning and AI.
More and more interactions are being handled or recorded electronically. All of them -- whether online, social, voice or messaging - can be
tapped for insights.
Machine learning (ML), natural language processing (NLP), and analysis technology help you crunch the data quickly and cheaply (although talent can be expensive!), if you can get access to sources. Admittedly that's a big "if," and ethics, bias, and privacy do come into play. The ethics concern does complicate the better-faster-cheaper triangle, but it's a must!
Data in hand, ML, NLP, and analysis tech let us explore new insight dimensions and link them to business outcomes. I'm particularly bullish on emotion insights. The aim is to tie sentiment and opinion to behaviors in order to create more responsive, more empathetic approaches.
Data and AI provide a gateway to new and better insights and from there to outstanding customer experience.
Seth Grimes
President
Alta Plana Corporation
The Social Network
Judging by the conversations I had in 2019, we enter a new year and a new decade with the acknowledgment that social data is a valuable source of consumer intelligence.
Organizations are realizing the uniqueness of social data in providing real-time, unprompted and authentic ‘voice of the customer’ insights and are utilizing it to make more informed decisions across their business.
The key to this is not viewing social data in isolation, but blending with other data sources to get a more complete picture and to understand causation and correlation that may exist.
Also important is an appreciation for social data’s strengths and the types of questions it’s good at answering. It is not a replacement for surveys, focus groups or other forms of research. It is, however, a great complement to them, and so my prediction (and my hope) for 2020 is that organizations will use social data to focus their focus groups, sharpen and shorten their surveys, and get to insights quicker and cheaper.
I also hope to see them get inspired by what they discover, for one of social data’s great strengths is in providing answers to questions you didn’t think to ask.
Joe Rice
Data and Enterprise Solutions
Twitter
Getting Started
Want to talk more about digital consumer intelligence?
Here's where The Social Intelligence Lab can help.
Getting Started
Best practice, expert opinions, unbiased advice and recommendations, a peer community and more...
The Social Intelligence Lab
The Social Intelligence Lab is a professional membership community for people running social intelligence programs at the world's leading brands and agencies.
We connect, educate and support our members to help them build stronger insights initiatives through language and conversational data, and other digital consumer intelligence sources.
Together, we challenge industry norms, discuss best practices, and are working to develop ethical standards.
Industry News, Opinion and Resources
Our content hub is updated daily with the latest industry news, opinion pieces, debates, best practice, and resources.
This is your learning platform to get information and support as you build out your digital consumer intelligence capabilities.
Never be left behind with new industry developments, discover best practice, case studies, and the latest industry news and tools.
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Clinics and Workshops
Sometimes you need unbiased support and advice from experts who really understand what you're trying to achieve and your reservations. We offer unbiased advice and expert training to help you get more value from social data and other digital consumer intelligence activities.
Our bespoke social intelligence clinics are designed to learn more about you and your business challenges. We'll identify your need for social intelligence or wider digital consumer intelligence, and how this can complement your existing insights stack.
Everything you need to get started on your journey or take your programs to the next level. Our clinics are perfect for brands looking to get serious about digital consumer intelligence. Or for those brands who have a license to a social listening tool but are not making full use of it.
Coming Q2 2020, we will be offering a series of workshops designed to develop your skills, and gain confidence in integrating digital consumer intelligence into insights capabilities.
Topics include:
- Query creation
- Integrating social intelligence with qualitative research
- Storytelling with data
- Bias, quality, and accuracy with social data
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Launching Q2 2020, our professional membership helps you to reduce risk and quickly increase success bu building a trusted peer network that understand the challenges of social media intelligence.
As a professional member, you'll join a private group of social intelligence professionals at the worlds leading brands and agencies.
You'll have confidential conversations online, by email and phone to discuss the problems and best practices you can't talk about anywhere else.
Everyone in the community understands social data and the challenges of social intelligence. They have the answers to the issues you are facing today because they're experienced and have been there before.
There's no vendors and absolutely no sales - only practitioners and senior leaders.
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Looking for the latest new technologies or in need of an agency to support your social intelligence programs?
Our Social Intelligence Matchmaking Service has all the latest tools, APIs, and service providers to help you find the right partners for you. Search our full directory here.
We also offer personalized and unbiased support to help you compare technologies and services, and select the right partners for your business needs.
Coming Q2 2020 - consumer and expert reviews for vendors and service providers.
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People and Companies
Information and contact details on the people
and companies featured in this report.
The People and Companies Featured
Get in contact and find out more about the people, companies, and approaches featured in this report.
The Social Intelligence Lab
The Social Intelligence Lab is a professional membership community for people running social intelligence programs at the world's leading brands and agencies.
We connect, educate and support our members to help them build great businesses from the intelligent use of their valuable language data and other digital consumer intelligence sources.
Together, we challenge industry norms and discuss best practice to help businesses get closer to their customers.
Website: www.thesilab.com Email: hello@thesilab.com
Brandwatch
Brandwatch is the world’s pioneering digital consumer intelligence suite, helping over 2,000 of the world’s most admired brands and agencies — including Unilever, Walmart and Dell — to make insightful, data-driven business decisions.
The company underwent an industry-transforming merger with Crimson
Hexagon in 2018, and has made three acquisitions to date: PeerIndex (2013), BuzzSumo (2017) as a standalone content marketing platform, and Qriously (2019) to add global survey capabilities.
Brandwatch has offices around the globe including Brighton, Boston, New York, London, Berlin, Stuttgart, Paris, Madrid, Sydney and Singapore.
Website: www.brandwatch.com
Email: info@brandwatch.com
LinkedIn: Bex Carson and Sabrina Dorronsoro
Audiense
The audience intelligence platform Audiense combines rich social data sources with machine learning and the leading cognitive computing technology.
Based on more than 800 million unique individual profiles, Audiense transforms social data into actionable audience intelligence that enables brands and agencies to obtain value from the insights from different channels, on demand and at scale.
Website: www.audiense.com
Email: Javier Buron
LinkedIn: Javier Buron
Ipsos UK
Ipsos provides a range of services to clients across all sectors, including social and other unstructured data sets, including qualitative data, survey open-ends, and pictures.
Website: www.ipsos.com
Email: Tara Beard-Knowland in the UK or Menaka Gopinath in the US.
LinkedIn: Tara Beard-Knowland and Menaka Gopinath
Converseon
Converseon.AI provides the world’s best social and voice-of-customer data quality and programmatic insight through AI-powered technology, ecosystem partners and the deepest industry experience (est. 2001). We have been active in the machine learning/AI space since 2008. We don’t just do machine learning for text analytics – we “do it right” and give you the tools to do so too.
We believe in an era where the collective voice of customers and citizens, empowered through social channels, will become a primary agent-of- transformation for governments, societies, industries, brands, and products.
Website: www.converseon.com
Email: Rob Key and Jane Quigley
LinkedIn: Rob Key and Jane Quigley
Listen+Learn Research
We are the Social Insight agency.
Since 2011 we’ve been using social data to help brands find, understand and appeal to consumers. Operating globally, we develop commercially applicable insights based on a deep understanding of human behavior.
We believe in the power of people to understand people - and use human analysis to make sense of social. We combine expertise in social and market research, marketing, communications, brand, and strategy. We understand the human experience and use this to help our clients create a bigger impact.
Website: www.listenandlearnresearch.com
Email: jeremy@listenandlearnresearch.com
LinkedIn: Jeremy Hollow
Storyful
Storyful is a global social media intelligence and news agency that partners with news and business organizations to make sense of social. It is a division of News Corp.
Website: www.storyful.com
Email: Jeff Perkins, Executive Director EMEA: jeff.perkins@storyful.com; Joanna Pitt, Executive Director of Brands EMEA: joanna.pitt@storyful.com; Fiona Thornton, Director of Sales, Brand and Insights EMEA: fiona.thornton@storyful.com
LinkedIn: Jeff Perkins, Joanna Pitt, Fiona Thornton.
Qutee
Qutee, the Social Asking comments and polling platform powered by AI analytics. Self-serve industrial-scale consumer research that allows you to create a super-sized focus group within hours understand thousands of opinions in real-time and download a comprehensive insights report.
Website: www.qutee.com
Email: twilson@qutee.com
LinkedIn: Tim Wilson
Nisa Bayindir
Consumer Psychologist
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Jim Reynolds
SocialGist
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Kristian H. Foged
Principal Insights and Analytics Consultant
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Preriit Souda
Data Scientist
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Kathy Doering
SMRA
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Seth Grimes
Alta Plana Corporation
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Joe Rice
Twitter
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