Imagine a product innovation pipeline fueled by smart investment in AI. Raw material trends could be sourced more easily. What was historically a manual and tedious process – R&D and marketing teams traveling around the world in search of the latest ingredients; procurement teams struggling to engage and negotiate selected raw materials within the timeframe of the launch; and finance teams working to forecast and create viable P&Ls – could now possibly be simplified into a few simple steps. Classical in-house use-testing could be scaled more easily, and packaging aesthetics could be tested through VR rather than manual and costly in-person testing. Custom or stock packaging can be sourced and developed collaboratively through AI and virtual reality.
Lockdowns Highlighted Process Inefficiencies
When running product innovation for a CPG company, I observed that it was very challenging for the cross-functional teams of R&D chemists, packaging engineers, innovation managers, marketers and visual merchandising designers to collaborate on a multi-million-dollar new product launch during the pandemic lockdown. Packaging options were reviewed on Zoom, which was particularly difficult for the custom-tooled portion of the design. The R&D team mailed the formulation submissions to each team members’ homes via FedEx and sent a survey to help prioritize the formula options. The team took turns driving into the office to look at elements of the new product that could not be replicated and mailed out for review.
This process is the bread and butter, so to speak, of how packaged goods companies create and market new products. The pandemic highlighted the vulnerabilities of these basic CPG practices. New product development commercialization is costly, time-consuming, manual and hit-or-miss. And while AI probably won’t replace the creative genius of successful cross-functional product development or a marketing team, it will certainly help streamline processes and drastically shrink the expense and timelines from concept to shelf, cupboard or bathroom vanity.
Lessons Learned from the Old Ways of Working
As products are commercialized, cross-functional teams work with finance partners and consumer insights teams to set the right price that the market will bear (with the retailer having the final say) and forecast product demand accordingly. If only one lesson was learned from the pandemic, it was that supply chains need to be nimbler to avoid both stockouts and over-production. In the future, better, more accurate forecasting will be available through advanced neural networks. This new technology is far more accurate than the traditional CPG forecasting models of the past. It not only incorporates lift metrics from marketing levers and historical averages of competing products, but also factors in industry outlook, competitive moves, cyclical factors, and demographic changes making it faster and far more accurate than traditional forecasting models. This will become even more relevant once cookies are out of the picture because advertising lifts will change (and will potentially be harder to measure).
Perhaps the biggest antidote to the cookieless problem is the advancement of first-party data. With data privacy laws and regulations tightening globally, the responsibility of owning and learning from internal data will fall directly on CPG companies. The good news is that most CPG companies own volumes of data across the omnichannel, including from internal call centers, DTC commerce sites, in-store retail, and social media properties, to name a few. The challenge lies in integrating these disparate sources of data to gain the most value.
Imagine an internal data source that incorporates consumer insights from every touchpoint and uses AI to filter through the noise and categorize findings for quick and easy insights. This end-state will also change the relationship with agencies, which used third-party data to develop media recommendations. The onus of understanding how best to acquire, retain and maintain customer relationships will fall more squarely on internal marketing departments. With a well-oiled internal customer data platform, analysis and decisions will become clearer.
If there was ever a natural selection test for the CPG industry, marketing without cookies will weed out the weak and the unprepared. The companies who are investing now are the ones who will win. And that’s just the way the cookie crumbles.