Why Customer Predictability Modeling Will Dictate CPG’s Winners in 2022

Business predictability concept

It’s no secret that consumer behavior is rapidly evolving in response to e-commerce acceleration and omnichannel adoption. 

In a digital-centric world, how customers interact and align with brands is far different — meaning CPG companies can no longer rely on retailers alone for sales and customer feedback. Their formula for fostering high levels of brand loyalty and business growth has changed. And while that change may be out of their control, what CPG companies can still control is how they react to it.

In turn, this societal shift requires a new, hyper-focused approach to engagement and forecasting only attainable through customer predictability modeling — a subset of interconnected digital transformation that leverages artificial intelligence and machine learning to generate actionable data insights on the probability of future outcomes relative to consumer behavior.

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Those insights can then be applied across multi-cloud integrations to deliver personalized customer experiences, meet evolving buyer expectations, and weather demand volatility. Above all, it empowers enterprises with the flexibility and foresight to pave new pathways for sustained success. 

The CPG winners of 2022 will be those who understand and unlock the power of multi-cloud customer predictability modeling. Put away your legacy technologies and siloed data sets. Say goodbye to your old operational business playbook. As consumers increasingly pivot to digital purchasing habits, brands must pivot in lockstep with digital transformation. 

The Data-Driven Personalization Effect 

From customizable product offerings to virtual product displays, the growth of digital adoption has caused customers to expect personalized experiences from every brand interaction. In other words, personalization is no longer just a “nice-to-have” capability in the CPG space. To meet evolving customer expectations, personalization is now considered a necessity. 

This widespread desire for personalization is a microcosm of a broader market trend across sectors. In 2021, companies that delivered personalization generated 40% more revenue than industry competitors. It was a direct ripple effect of an increasing willingness from consumers to abandon brands that don’t meet their expectations. Nearly 75% of U.S. consumers tried a new shopping behavior in response to poor personalization, while more than 40% switched brands altogether. 

With customer predictability modeling, brands can take proactive steps to ensure every customer interaction is fully personalized. For example, by automating the analysis of multi-cloud e-commerce data on omnichannel behaviors and digital purchasing trends, brands can offer repeat customers auto-replenishment options for a seamless online buyer’s journey that mirrors the in-store experience. 

They can also tailor discounts based on frequently purchased product combinations, as well as optimize inventory levels to navigate demand volatility and supply chain disruptions that often cause out-of-stocks. 

Brand Advocacy Through Data-Powered Loyalty Management 

The average U.S. consumer is switching brands more than ever before, highlighting the need for companies to prioritize building and maintaining customer loyalty at every touchpoint. Fostering consistent loyalty can be accomplished by leveraging customer predictability data to develop a deeper and more intuitive understanding of consumer expectations and pain points. With real-time visibility into both the former and latter, brands can enrich their loyalty programs with the right incentives that best resonate with buyers and build lasting relationships. This helps create a data-driven loyalty ecosystem that delivers lifetime value by: 

  • Increasing repeat spending and purchasing frequency
  • Driving customer referrals and new revenue 
  • Creating upselling and cross-selling opportunities 
  • Boosting partner engagement and performance 
  • Strengthening brand advocacy and awareness 

From a B2C marketing standpoint, extensive loyalty program data helps identify “brand champions” to serve as ambassadors who drive brand-customer interactions — ranging from sharing new product offerings and testimonials on social media to providing organizations with key customer engagement insights that dictate sales potential. With a robust pool of ambassadors across target verticals, brands can then build online communities of power to fuel rapid growth and sustained success. 

In today’s digital age, customer predictability modeling is a brand’s most valuable asset. However, their data is only as strong as their ability to act on it. Embracing the full potential of customer predictability modeling will be a fundamental aspect of capitalizing on digital transformation. By leveraging the enormous amounts of data at their disposal, CPG companies can achieve business outcomes that separate themselves from industry competitors for years to come. 

—Gerry Szatvanyi, CEO of OSF Digital

About the Author

Gerry Szatvanyi

Szatvanyi is the CEO of OSF Digital, a top digital transformation and leading global commerce solutions company to some of the world’s most well-known brands.

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