Anyone can publish their opinions, their passions, their interests, spontaneously, and with great reach, anywhere, any time, and their stories can be viewed through any connected device. This has revolutionized the way brands understand, communicate with, and engage with their consumers.
In her Internet Trends 2019 report, the American venture capitalist and former Wall Street Analyst, Mary Meeker, said “The rapid rise of gathered / analyzed digital data is often core to the holistic success of the fastest growing & most successful companies of our time around the world”.
The stage is set. To be successful, brands must embrace an agile and customer-centric culture rooted in AI-enabled consumer intelligence.
Many of the world’s most successful and loved brands, including Nike and the Procter & Gamble Company, understand that being attuned to the voice of the consumer is what makes them more authentic and sets them apart.
Leading brands have reinvented the way they achieve consumer intelligence to meet fast-evolving consumer needs and preferences by combining new technology and classical research approaches to process millions of online posts and conversations. Their ability to innovate, plan and execute their product, marketing and customer strategies, and ultimately to maintain leadership, depends on this.
What is consumer intelligence?
Consumer intelligence (CI) is the process of gathering and analyzing information about customers and potential customers to better understand them and avoid using preconceived ideas about “what we think they think” to build deeper and more effective customer relationships and make better informed decisions. It’s the foundation of all strategic marketing.
Bringing consumer intelligence into the digital era, AI-enabled consumer intelligence uses technology to retrieve and analyze billions of online data and allows brands to understand consumers faster, deeper and in a consistent manner.
A case study
Pernod Ricard, the world’s second largest wines and spirits company, uses AI-enabled consumer intelligence to understand people at every stage of the consumer and shopper journey, including early on when they’ve only just started considering a product or are seeking one that resonates with their needs.
They deep dive into unsolicited and spontaneous consumer conversations and, with context and sophisticated data structure, provide the business with real insights and actions.
Staying ahead of the curve: Why brands must adopt AI-enabled consumer intelligence
The need for global consistency
A big challenge for global brands is maintaining a globally consistent brand promise, while still remaining locally relevant.
AI-enabled consumer intelligence democratizes insights within the organization, making data available and actionable in a consistent and relevant manner from marketing and consumer insights to IT. Data can be seen as a single source of truth within the organization. It provides global governance, while still empowering regional teams to customize their activities to local circumstances.
AI-enabled consumer intelligence helps global organizations ensure that methodologies and metrics are consistent across brands, teams, and locations. The growing needs for intimacy, authenticity and relevance.
The emergence of new consumer behaviours has changed the way marketing professionals do their job. They must rethink the way they do marketing. They must become more consumer-centric, more agile, and faster. However, many brands are still struggling to find authentic and innovative ways of relating to people and audiences authentically and finding consumer-centricity.
AI-enabled consumer intelligence is also a way to be responsive to uncertainty. Listening to what is said online in real-time allows brands to quickly understand the main concerns, challenges and questions poised by consumers, and gives brands a glimpse of everyday reality they might have ignored otherwise.
For instance, the COVID-19 crisis demonstrated that new concerns can surge suddenly and disrupt the way people interact, think, and live. With consumer intelligence, brands can tailor their content and communication quickly and demonstrate the responsibility and support consumers expect.
What does AI-Consumer Intelligence mean for the future of market research?
The limitations of market research
Within the new customer-centric, digital paradigm Consumer & Market Insight departments need to deliver actionable insights faster to enable informed decision making across the entire organization. they are under pressure to transform their processes to stay in front of consumers and do more with less:
- While retrospective analysis and quantitative recall studies help to understand the past, they are not enough to map out the future fast enough. Identifying intent and consumption moments when they happen gives businesses a better chance to address shifting demand.
- The geographical limitations and cost implications of running traditional research in multiple markets are becoming harder to justify. Research budgets are often first to be cut or reduced and the danger of losing sight of valuable insights has increased.
- While focus groups and surveys are a fundamental part of the research toolkit, bias is often created in the way traditional surveys are built. Listening to unsolicited and spontaneous expression is critical to understanding consumers as they see themselves and should be integrated with classical methods.
AI-Enabled Consumer Intelligence must complement traditional market research
Generally accepted as the next generation of market research by CMOs and analysts alike, AI-enabled consumer intelligence allows brands to harness the voices of consumers and conversations from all public, social, and digital spheres and get insights as deep as traditional market research without being lengthy and costly.
In a survey of over 50 global brands, exploring current and future use of classical and AI-enabled insights, marketing leaders shared their plans for 2021: 75% plan to complement classical methods with AI-enabled consumer intelligence.
Classical and AI-enabled consumer insight should coexist within the organization to ensure brands have a full picture of their consumers, markets, competitors - which is as close to real-time as possible and consistent across markets.
Serving the needs of the full brand life cycle
Let's take a look at the brand life cycle:
In a world where the competition is fierce, brands need to STRATEGIZE. The first step in creating, refining, or optimizing a market strategy is marketing intelligence. A fundamental understanding of consumer needs and desires, market trends, competitor positioning, and how all of this manifested in marketing communications and product offerings is the foundation of the brand life cycle.
Traditional market research entails multiple methodologies, including surveys, interviews, focus groups, and more purpose-designed types of ethnographic research, Done in static moments in time, these are fundamental to the brand lifecycle framework and give a snapshot of the current attitudes and behaviors of consumers.
By integrating the frameworks of these traditional approaches with AI-enabled consumer insight, researchers and marketers turn this snapshot into a “living view” of brand and consumer strategy, giving them agility to guide strategy based on the overnight changes that happen based on the digital nature of modern consumer lifestyles.
Brands must benchmark the competition to understand the battlefield and to define their go-to-market strategy.
For example, in terms of one of these strategic initiatives, audience segmentation, social media has overturned the ways consumers identify, bond, and communicate. Rather than demographic association, consumers seek authentic and meaningful connection based on shared interests and values. This means that marketers have to go beyond the traditional socio-demographic segmentation to identify tribes of interests to target.
A tribe is a group of like-minded individuals who actively interacts with each other, looking for authentic and meaningful engagement, based on shared interests and values.
Their bonds are more powerful than their demographic group, because a tribe is defined as a network of heterogeneous persons - in terms of age, sex, income, etc. - who are linked by a shared passion or emotion.
Audience segmentation is key when it comes to positioning. Understanding who is their key target, brands will be able to define which topics will resonate with their target audience and connect with it with an authentic voice, showing dedication to their shared passions and behaviors, and by addressing their cultural and societal purposes.
AI-Enabled Consumer Intelligence crosses qualitative and quantitative analysis to avoid bets and intuition to define the perfect messaging that will resonate with the target audience.
With a living strategy defined, it's time to EXECUTE. The introduction of products, communication of features and benefits of the brand, functional and emotional, and management of a complex omnichannel campaign, both offline and online, is a highly evolved skill set that requires a highly evolved technology stack.
While it’s now well-accepted that digital marketing is the basis of customer-centricity for modern brands, it’s less established that the inspiration and tracking for marketing execution should have an equally strong data-driven approach.
Connecting to the audience example above, influencer marketing is one of the most critical applications for AI-enabled intelligence. Defining a reliable influencer network to relay authentic and trusted messaging means identifying influencers that both a) correspond well with the brand's image and communication strategy, but who are also a member of the tribes the brand aims to target. Social intelligence allows brands to automatically track tribes as the shift, grow, merge, and diverge.
Understanding the voice of the customer in real-time is fundamental for brands to fine-tune their execution. Listening to feedback on consumer review sites allows brands to adjust, engage conversations with disappointed customers, to amplify positive experiences, and to turn detractors into advocates. This even empowers brands to improve their search performance or trade marketing.
A crisis can come out of anywhere, and PR and corporate affairs teams must respond swiftly to protect the brand.
The best chance to make it through a social media crisis is to prepare ahead of time. Brands must monitor all conversations related to their brands, industry, and influencers, and define a crisis assessment and action plan based on potential scenarios. In addition to managing a crisis, it is equally important to measure impact on brand reputation.
To identify crises early, communications and PR managers must track sensitive topics over time along with related mentions of the brand. This is one of the first business use cases that social listening offered to solve and it is still essential. AI-enabled Consumer Intelligence can bring a deeper-dive analysis to measure brand reputation in terms of brand pillars, relative to each consumer tribe.
Once integrated cross-channel campaigns are launched, brands must stay agile with a test & learn approach. For that, they must MEASURE their performance.
There are 3 ways to do this:
- Campaign performance: Measuring the reach & engagement of marketing campaigns across owned and earned media.
Good campaign strategy requires great analysis. Brands must track marketing campaign performance, measure their effectiveness, and use this data to adapt the current campaigns instantly and make the next project even better.
- Customer experience: Understanding what the customers say by analyzing customer experience to fine-tune campaigns but also to adjust product strategy.
Analyzing customer experience helps also to measure the performance of marketing campaigns. Listening to consumer feedback will allow brands to meet customers’ expectations and win their loyalty. With the emergence of online ratings and reviews, brands can count on a solid methodology to analyze quantitative and qualitative data and make sure they will harness customers' voices.
- Brand equity tracking: What is the impact of campaigns on brand equity? Are they reinforcing strategic brand goals, and establishing consistency?
Even if brand trackers are traditionally a fundamental tool for market research, brands should complement traditional survey-based trackers with AI-enabled consumer intelligence to understand equity in real-time, with the ability to filter by awareness and perception driver, and “ask-multiple questions afterwards”.
To survive in this competitive world where not only are multinational brands introducing hundreds of new products a year, but where startups are disrupting the industry constantly with entirely new product concepts and service models, brands need to INNOVATE.
Via always-on insight based on structured data specific to the brand’s category, organizations can detect weak signals and emerging trends to “nearcast” what consumers want, and create compelling products and experiences ahead of the competition.
AI-enabled consumer intelligence enables brands to use the power of AI and data science associated with a methodological framework to have a clear picture of what will shape the future of their industry and innovate before the competition.
After new product introduction, brands can track customer experience by monitoring social media and consumer review sites in real-time to understand fast-evolving consumer needs and preferences, in terms of brand, communications, product, packaging, and every consumer touchpoint.
The brand life cycle, democratized
As a theory, the product and brand lifecycle dates back to the 1950’s, and has continued to be a textbook framework for marketing management until today. However, while the model remains valid, the marketing intelligence tools used to inform it have not changed significantly, while consumer behaviors and the media environment have.
In order to keep up with the speed of changing culture, especially digital and social media culture, brands must complement classic methods with new technologies born in the same era that their customers came of age: AI-enabled consumer insights.