Burgeoning Board interest in creating a data advantage doesn’t always translate into understanding of the consumer insights/analytics connection. Insights and analytics are two sides of the same coin: one can’t exist without the other. In the words of Nick Rich, former VP of Insights & Analytics at Carlsberg: ‘Leaders love analytics because everything adds up to 100.’

Most organisations and leaders aren’t using data effectively – because they haven’t connected it. Eight in 10 business leaders say data is critical for decision-making, but only half truly understand their data. Only 40% of available data is actually used in decision-making, in part due to a vast array of BI tools, with 1 in 4 organisations using more than 10. Engaging decision-makers in data connectivity relies on communicating the value of insights in driving business growth.

Organisations already have enough data: insights and analytics leaders are focused on creating more value from their existing data sets, not commissioning more research. Vendors in turn are focused on delivering the easiest access, simplest data queries and most intuitive meta analysis that heighten insights into strategic tools for advantage.

Realising the Direct Impact of Data Connectivity on Company Goals

Your Board is naturally and continually striving for greater agility and profitability. A 10% increase in data usability can generate $2 billion in revenue for the average Fortune 1000 company. Organisations that report ‘extensive use’ of consumer analytics capabilities also report 93% higher profits than competitors.

Stakeholders can better understand the link between data connectivity and profitability potential through real-life examples of how critical insights can deliver on KPIs, such as:

• Optimising digital advertising campaigns to generate £Xxmillion in sales
• Leveraging conversational data from chatbots to improve customer satisfaction and loyalty
• Linking brand awareness and consideration to the revenue generated by brand equity
• Uniting campaign tracking and POS data to forecast the best areas for investment and tangible return
• Identifying opportunities for bespoke product development and innovation to dominate niche categories.

Sharing how new ways of measuring (and then improving) the consumer experience will help leaders steal market share where competitors are failing to deliver. Specifically outlining the role of connected data sets in a holistic consumer view reinforces the power of a consumer mindset in key stakeholder decision-making.

Stephan Gans, SVP, Chief Consumer Insights and Analytics Officer at PepsiCo, shares how his team communicates the value of data connectivity for business growth: ‘The way I like to talk about it is global might for the local fight. A company is thousands of islands where everybody’s doing their own thing. Getting the insights leader at the table when commercial decision-making happens is one step. But driving consumer-centricity at the point of all commercial decision-making comes down to empowering the people in the room when decisions are being made. Those people need the potential to leverage the wealth of data, for valuable insights that enhance competitive advantage on the spot. Data connectivity is about creating the federal structure that enables all your islands to thrive, leveraging their skill for advantage.’

‘You’re not just a data scientist or a technologist, but a team builder who must bring together the right mix of skills and talents to harness the power of data.’

Harry Powell,
Head of Data and Analytics at Jaguar Land Rover

Demonstrating the Role of Data Democratisation in Business Growth

To deliver seamless, personalised and engaging consumer experiences, your teams need deep expertise in their own fields supported by real consumer understanding. Comparing examples of current team data use against the wide range of unrealised data sources contrasts existing limitations with future business impact. The innovation potential of teams who can leverage connected data will help leaders pivot into new categories and gain early competitive advantage.

The difference between data-informed and data-driven teams is a question of the right training. Stephan Gans simplifies, ‘Meta-learning is just a fancy way of saying: ‘Let’s do your homework’. But when you digitise the process and you standardise the tools, suddenly you’re creating this wealth of skill that you can leverage.’

‘AI will augment everything your whole organisation already does,
answering every business question on a deeper level’

Martyn Crook

Communicating the Impact of AI-Powered Insights on Sales, Marketing and Business Performance

Connectivity enables teams to mobilise profitable opportunities, but AI will take insights potential to the next level: faster data means faster analysis that empowers faster action. Presenting how AI-driven connectivity will link insights data to other datasets will show executives that they can get faster answers to business-critical questions, to achieve the agility and profitability they need on a larger scale.

AI’s capability to enhance marketing impact can be demonstrated by revealing its role in instantly measuring effectiveness to improve innovation, consumer experience and competitive advantage faster. From annual planning to brand proposition to campaign optimisation, combining big and small data will reveal and improve the potency of all touchpoints. Although data connectivity will provide the full picture of upcoming commercial opportunities, LLMs will summarisethis research instantly. ‘In-the-moment’ marketing analysis improves operational efficiency in real-time to accelerate incremental revenue.

AI will also have a pivotal impact on how marketing teams deliver better consumer experiences. Global advertising spend reached $754 billion in 2024 – but much of this spend has yet to deliver tangible results, because emerging technologies are not being deployed in understanding the consumer journey. The CMO Council reports that just 5% of marketers have the ability to respond to campaign data in meaningful ways in real-time, and the majority cannot predict future consumer needs. Biljana Cvetanovski, McKinsey Partner elaborates, ‘Whilst marketing leaders recognise the importance of using AI to drive growth, there’s a 25 percentage-point gap between the importance they place on developing generative AI capabilities and their ability to execute them. Marketers who act can gain a substantial competitive edge.’

The optimum consumer experience of the cookieless future is only possible with optimum consumer insights. Whereas search activity tells only half the story, GenAI identifies unrecognised fears and hidden needs. AI can deliver immersive AR/VR experiences and hyper-personalised content at scale, boosting revenue by 20%. AI-powered insights are the best tool in the marketers’ armoury to reveal unconscious emotional purchase drivers, predict consumer behaviours enhance campaign effectiveness.

On the unparalleled potential of AI to improve the consumer journey, Elaine Rodrigo, Chief Insights & Analytics Officer at Reckitt shares, ‘AI can be a huge enabler to integrate all our data and insights across the E2E consumer journey. Starting with what drives category demand amongst our key audiences, we can understand all touchpoints across the journey and how to activate each one to drive conversion and build the brand.’

How Unilever Uses AI to Evidence the Value of Data Connectivity to Senior Stakeholders

Unilever’s shift from purpose-driven brand to performance-driven business was underpinned by engaging senior stakeholders with connected consumer insights.

Unilever’s CMI function uses AI to integrate forecasting and actual sales data in real-time, with cross-functional teams accessing insights from an in-house cloud platform. Automatic daily processing of large, complex and unstructured consumer datasets from social media and product reviews shares the Digital Consumer Voice across the organisation. Machine learning-based natural language models analyse consumer sentiment and identify key consumer conversation topics. AI-powered connected data equips marketing, quality and research teams with the self-serve insights to react swiftly to trends and consumer feedback. Unilever’s insights-driven decisions have already improved product quality, enhanced consumer experiences and delivered cost savings of €350k in individual cases.

Connecting and democratising data with AI has transformed consumer insights into actionable strategies – but this is only possible with continual stakeholder engagement. CEO Hein Schumacher uses earnings calls to align consumer insights with stakeholder interests. Schumacher recently emphasised that only 41% of Unilever’s business was winning market share on a rolling annual basis, but that AI-driven consumer insights would influence better predictive modelling that identifies opportunities to reach new consumers

‘Real-time analysis shouldn’t always mean real-time action.’

Martyn Crook

Sharing the Right Insights to Inform the Right Decisions

30% of business leaders are overwhelmed by the amount of organisational data available. Accelerated use of AI to connect a wealth of real-time sources can result in multiple versions of the ‘truth’. Fast-changing consumer sentiments like political and social attitudes – and their impact on brand perception – can be misinterpreted, leading to premature knee-jerk decisions that pressurise teams for rapid but unstrategic change.

Instant insights don’t always need to be delivered immediately. Senior leaders need structured reporting windows to ensure insights are actionable rather than overwhelming. Curating insights to inform the best (rather than the just the fastest) decisions involves differentiating between which insights are automatically delivered to stakeholders, and which are first interpreted by relevant data analysts.

Andrew Chen, former Head of Rider Growth at Uber shares the importance of demonstrating to stakeholders how connected data can help them prioritise: ‘Don’t let shallow analysis of data that happens to be cheap/easy/fast to collect nudge your stakeholders off course. Present them with the right data and map it down into small enough pieces to execute in a data-informed way.’

How Coca-Cola Unites Sales & Brand Tracking to Connect Data & Insights for Senior Stakeholders

Coca-Cola’s own AI-driven ecosystem forms a single source of consumer truth by aggregating data from 300 brands, 100 sources and 75 agencies globally. The entire cycle of brand and sales activations is made visible across the organisation by combining data from:

• Advertising campaign performance
• Chatbots
• Customer satisfaction surveys
• Conversational data from social media interactions
• Cultural trends
• Immersive AR and VR experiences, such as virtual tours of production processes and interactive brand stories
• Limited-edition product and packaging testing with advanced sensory technology
• IoT-connected vending machines that collect real-time POS data
• Localised weather patterns
• Purchasing habits and history
• Sales reports.

Coca-Cola’s plethora of brands, categories and geographies requires seamless integration of consumer data across segments, cultural tribes, locations and purchase occasions. A globally scalable capability allows for region-specific customisation, to reveal international market trends and interpret their impact on smaller local markets.

Real-time telemetry provides stakeholder visibility of how campaigns influence consumer awareness, resonance and action across markets. Delineate unites Coca-Cola’s research and global campaign tracking data to give senior stakeholders a detailed picture of the holistic brand experience across 50 countries. Machine-automated market research scales analysis of daily interactions and instant brand recall across touchpoints.

The company’s AI tools cascade partner data into one accessible dashboard that can be customised by different teams to visualisegranular findings. Coca-Cola’s insights teams transitioned from monthly field research to a speedier cadence, answering key business questions in hours to optimise campaigns in-flight. AI delivers faster answers that help Coca-Cola’s insights team optimise campaigns in-flight, to improve effectiveness and in turn marketing and sales impact on business growth.

Imagine your entire organisationleveraging data (almost) as effectively as your insights team. Impossible? Not with the right approach.

Securing an Executive Sponsor to Encourage the Best Cross-Functional Data Usage

Designating a senior champion mobilises your stakeholders as data connectivity advocates. Executive sponsors can elicit team curiosity around applying AI to data learnings and encourage calculated AI-informed risk-taking. Chief R&D Officer Najat Khan set up Johnson & Johnson’s enterprise-wide Data Science Council to track the value of scalable consumer insights from democratising GenAI across the organisation.

Preventing Data Overwhelm

Segmenting your teams by attitude and skill informs tailored communications for the brave new world of data and AI. Your most reluctant teams will require in-depth training and information to mitigate data privacy. Content on productivity-enhancing automation can engage the time-poor, and AI enthusiasts will embrace updates on new tool features.

Delivering Data & AI Literacy Training

75% of the workforce believe Artificial Intelligence will accelerate job losses, with over half of younger professionals particularly concerned. The best data literacy training creates a mindset of working with AI, not for (or against) it.

Teach employees what data they don’t need. Nick Rich expands, ‘We could have better realised the value of our data if we’d connected macro and meta-data projects as technology was becoming available. The greatest successes of collaborating come from a reductive data focus.’

How Nestlé Uses AI to Democratise Data & Insights to Stakeholders

Nestlé partnered with IBM and used Microsoft Power BI and Azure to build a central business intelligence hub that democratises consumer insights. The AI-powered Customer Data Platform integrates data from 20+ brands to share a holistic view of consumer interaction with D2C channels, promotions and campaign landing pages company-wide. Automated demand signal-driven forecasting suggests new concepts in just over a minute, empowering teams to test creative ideas and get innovative products to ready markets quicker.

Nestlé’s FAIR (Findable, Accessible, Interoperable, Reusable) data framework  guided framework guided democratisation training for 40,000 ‘Citizen Analysts’ across the company. The Freedom Box approach gave teams the autonomy to explore analytics according to their individual competencies, and instilled accountability for the insights they developed.

The Biggest Problems Leaders Face When Scaling Access to Insights

Selecting the wrong connectivity solutions for growth.

Chief Digital Officer Sandeep Dadlani reveals how Mars scaled data connectivity: ‘We set up data lakes and a vendor ecosystem that has hundreds of petabytes of data. Now we are in a position to move forward in the data and analytics journey meaningfully.’ Mars’ infrastructure investment advances digital transformation capabilities as team competencies mature.

Failing to equip teams to handle increasing data velocity and variety.

As data volumes grow and organisational analytics capability evolves, insights leaders must find a balance between self-serve use and expert supervision. Brian Balfour, former VP of Growth at HubSpot advises on scaling data training, ‘As you gain fresh insight from your data, it opens the door to new questions. Saying the process is “done” is saying you understand everything there is to know about your users, product and channels. As you have new questions, you need to update your instrumentation and analysis.’ User-friendly platforms with built-in visualisation tools reduce the learning curve in translating complex data sets, but training and stakeholder collaboration are key to develop commercial insights as analytics understanding evolves.

Underestimating future governance challenges.

Mark Ramsey, former Chief Data Officer at GlaxoSmithKline, advises: ‘Effective AI-driven governance is less about control and more about the flow of information to manage increasingly diverse sources of consumer data.’

How PepsiCo Develops AI Tools with Partners to Scale Data Democratisation

PepsiCo transformed its global capability from manual reports to AI-powered analysis by building Ada, its centralised consumer insights ecosystem that democratises data from 95 million menu items, 226 billion recipe interactions and 22 billion social posts. Teams employ Natural Language Querying to ask questions through Google-type searches, using sentiment analysis and promotion effectiveness insights gathered in one region to inform decisions across locations.

Shifting from a rigid BI model to a self-service approach sees regional teams filter data, customise interactive dashboards and deliver sophisticated basket analysis independently. One-click AI-assisted reports share drillable views and scorecards across departments to inform market segmentation by need. Senior executives receive regular curated communication on the most relevant insights and recommendations.

The company’s insights team co-develops IPs and market-facing AI tools with agencies, filling internal skills gaps with external expertise to scale consumer knowledge. PepsiCo’s insights leaders have become a source of answers for critical consumer questions, whilst all teams adopt advanced ML to create more personalised consumer experiences and speed up decision-making.

There’s never been more data – but you’ve never had a better opportunity to harness it. The best consumer insights are supported by the best data partnerships.

Delineate’s always-on tracking captures consumer data across all communications channels in real-time to instantly connect you to global audiences. Gain the competitive advantage enjoyed by Coca-Cola, Ancestry.com and Nomad Foods: get insights on demand to make the best business decisions fast.

Here’s how Delineate can skyrocket the impact of your consumer insights.