What is AI-enabled consumer intelligence (AICI) - and why should you care?

To say that these days it’s hard for brands to keep up with shifts in consumer behavior is an understatement.

Over the past two decades, digital advances have been changing the game and balance of power between brands and their customers. The ubiquity of broadband and mobile, online shopping, and social media led to the rise of new consumer practices like showrooming, purchasing from marketplaces, and posting to ratings sites. And launched a new generation of Instagram and TikTok influencers.

And then COVID hit. Online shopping spiked. Working from home became the new normal. And social connections took on a new meaning. McKinsey reported in May 2020 that consumer and business digital adoption vaulted five years forward in around eight weeks.

With social changes, many consumers have also started to ponder what they want from their brands, beyond a transactional relationship. Do they value what I value? Are they committed to causes that I support? In fact, Ipsos has found that consumers do indeed want deeper social-justice commitments from brands.

It’s a brand new world, and more companies are revamping their insights infrastructure to keep up. As Edmond Mesrobian, retailer Nordstrom’s CTO said to Venturebeat: “We had to figure out how to get analytical data to make predictions that help us make additions, so that we can actually offer the most compelling experience to our customers.”

While Nordstrom’s approach assembles open source and cloud components, a number of vendors are doing the same and packaging them up with services to allow brands to gain more holistic, more real-time consumer intelligence.

Introducing AICI and the search for unknown unknowns

As defined by Forrester, AI-enabled consumer intelligence (AICI) platforms "enable enterprises to use insights from data from outside their firm (e.g. social, web, and/or consumer data) and combine it with their own data (e.g. CRM, website) to optimise the experience of their current customers. Further, they look beyond firms’ current customers’ behaviours, needs, and preferences, rapidly delivering actionable insights on emerging trends, outliers, and unexpected shifts or changes in consumer behaviour."

The ability to see outliers and unexpected shifts is core to AICI. Surveys are a proven way to track consumer attitudes – when you know the questions to ask. But AI (and especially unsupervised machine learning) can help to spot unknown phenomena – answers to questions you didn’t yet know to ask. Or the so-called “unknown unknowns.”

For example, many businesses have been focusing on employee attitudes about work after COVID, working from home, and returning to the office. In these surveys they often focus on preference about work schedules and challenges or benefits of working at home; the known questions.

But when you point AICI tools that include topic and trend analysis at what employees are actually saying and doing online, a more complete picture emerges.

When analysing conversations around returning to the office, you first see clusters of themes representing known topics like vaccination or commutes. But AI-powered clustering is also remarkably effective at finding and naming emerging themes. In this domain, you also see lesser-known topics like salary (“I need to get paid more if I have to go into the office”) and fashion (“what will I wear when I go back?”).

Being the first to see these emerging trends creates first mover advantage, especially for EX teams tracking employee retention, or marketers planning their next campaign.

Forrester maps the AICI market – and ranks the leaders

Among its ongoing coverage of AICI platforms, Forrester has mapped the landscape of top and emerging vendors. According to the firm there are 26 of them overall, per the firm’s New Tech published in June 2020. These providers have roots in categories such as social listening, social suites, customer engagement, or market and competitive intelligence.

As a follow-up to this first study, the firm just published its assessment of the top nine vendor in The Forrester New Wave: AI-Enabled Consumer Intelligence Platforms, Q3 2021 – available to Forrester clients or here from Synthesio (brief registration required).

Forrester’s assessment looked at 10 criteria, 7 related to product capabilities, and 3 related to strategy (vision, roadmap, market approach). When the firm finished crunching the numbers, Talkwalker, Synthesio and NetBase were named as “Leaders,” Sprinklr, Brandwatch, and Linkfluence were ranked next as “Strong Performers,” Resonate and Digimind were next as “Contenders,” and Khoros was the one “Challenger.”

For marketers and insights pros, this ranking can provide a shortlist of vendors to evaluate for your AICI initiatives. But another way to look at providers is by what type of solution they offer. If you mash up these results with Forrester’s AICI segments from their New Tech - Software platforms, Service providers, and Hybrid platform/service providers, you can get a feeling for who is best for selling you tools (if you are into DIY and have a high level of maturity), pure consulting services, or a mix of both.

Through this lens, Talkwalker is the top rated Software platform provider in the Wave, and Synthesio is the top rated Hybrid platform/service provider. Noting that none of the service-focused providers in the New Tech qualified for the Wave.

It’s more than getting your data together

When we talk about getting a more holistic view of you customers, of course the topic and role of CDPs comes up. And in practice, data from your CDP should feed your AICI platform. Just as AICI-sourced consumer insights will feed your CRM or Business Intelligence system to support decision makers in corporate, or sales or product teams.

But much of the data flowing into your AICI will be unstructured. And while technologies like social listening or VOC gives you a view into what consumers are saying in posts or surveys, AICI mashes this up and breaks down silos. It’s also inherently multi-domain, and multi-language.

But the real power in AI-enabled consumer intelligence lies in the “AI” part. To process and clean your data, and deliver more accurate results. Leading AICI platforms provide intelligent search and natural language processing (NLP), often built on top of open source tools like Google BERT.

Top ranked solutions also include tools for topic modeling, using the power of machine learning. Allowing teams to spot cultural shifts, brand moments, and unmet needs - like to the fashion example above.

It’s ultimately about being predictive. As General Mills CMO Ivan Pollard discussed in a recent conversation with Marketing Dive. “Internally, we’ve gotten a lot more focused on the power of data to predict. We’re taking our insights teams now and making them as much intelligence teams as they are insight.”

So the potential here is a new era of market research, where AI-powered analytics and consumer insights are available to the masses, allowing marketers, CX teams, insight pros and the organisations they support to get closer to the holy grail:

• See what customer are saying and thinking about your brand, in real-time.
• Understand broader cultural and market-level shifts, while having confidence in what the data says.
• Make more agile go-to-market decision, based on these insights.
• Anticipate the next product trend, by seeing sparks of innovation before they are mainstream. Then baking those into your product strategy.
• Spot your next competitor, or your next partner (or M&A target). Then building positioning strategies to meet them there.
• Know which type of client or employee is happy or ready to churn. Before they tell you. So you can update their next experience with empathy and attention.

But like any other emerging category, the early days of AICI requires human-machine teams, blending both proven insights know-how, and new-age AI-powered innovation and discovery.