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Consumer-Level Data Combined with AI/ML Helps Retailers Understand Demand and Align Merchandising and Marketing

  • Michele Fitzpatrick

    Michele Fitzpatrick

Consumer-Level Data Combined with AI/ML Helps Retailers Understand Demand and Align Merchandising and Marketing

In retail, there has historically been a wide divide between merchandising and marketing. Marketing knows a lot about the people who buy their brand’s products while merchandising knows, in the aggregate, what’s been bought and sold in the past.  As a result, there can often be significant misses in the alignment between inventory and sales. 

And then the COVID-19 pandemic hit.  Things got worse.  All the historical understandings about what people are likely to buy, or what they’ve bought, no longer apply.  That’s because in addition to changing HOW they buy; consumers have also changed WHAT they buy.  People are buying more essentials, and less fashion and luxuries.  They are spending less overall.  And that has created an inventory planning and deployment challenge for retailers that is an even bigger deal.

As we reflect on all the pandemic-related disruption in 2020, two things are abundantly clear:  first, consumer shopping and buying behaviors have changed significantly, and second, we’re never going back to pre-pandemic purchase patterns and behaviors.

The big headlines for retailers everywhere have been about the acceleration of digital and contactless shopping and buying behaviors — more than ten years of acceleration in ten months. What people aren’t talking as much about is the supply chain disruption.  And that is an even greater challenge for retailers.  

Merchandising and marketing are typically separate functions.  Inventory planning is done four to six months or more ahead of the season, while marketing planning is done much closer to the season’s start.  What’s more, merchandising decision making is typically conducted based on historical, aggregated data, while marketing decision making is typically done independently and is based on customer-level data.  So, each function uses entirely different data and inputs in their siloed planning functions. 

This separation between functions – under normal conditions – creates data and insight gaps resulting in misaligned inventory and lost revenue and margin.  This gap in precision for planning has been completely exacerbated by the pandemic and the supply chain disruption it’s caused.

At Acxiom, we’ve developed a solution to close this gap  by applying customer-level data that’s been optimized for marketing to quantify true market demand. Using this data in combination with AI/ML intelligence helps planners and buyers understand and quantity true market demand so they can predict, measure, and optimize inventory planning and allocation processes more precisely.  Inventory can be based on  customers and prospects in the market around a store or in a region.  This consumer-level view of the inventory helps more precisely inform and optimize promotion planning, and pricing strategy

Additionally, this data-rich view of the true market demand can be used by marketers to inform marketing and promotion plans based on the consumers in a market and what specific sku’s or categories they are likely to buy in a particular week. 

The same data and the same platform are used to inform both merchandising and marketing in a way that fosters collaboration and thus begins to close the gap between merchandising and marketing.  When this occurs, retailers can better align merchandising and marketing to increase revenues and margin while reducing overstocks, out of stocks and over-dependence on discounting.

Here are a few of the use cases for this combination of consumer-level data and AI/ML technology:

  • Forecasting:  Inventory forecasting and product lifecycle management are in tune with customers and market potential
  • Products:  Inform sourcing and product mix for customers and market potential
  • Margin optimization:  Optimize margin for seasonal merchandise and product lifecycle
  • Inventory/markdown:  Optimize merchandising and inventory plans in alignment with revenue fluctuations by season
  • Customer intelligence:  Leverage data generated by all channels and business processes to quantify true market demand and align merchandising and marketing
  • Marketing:  Alter marketing outreach to improve sell-through, revenue and margin

Acxiom has developed a solution that uses first-party and third-party customer-level data and AI/ML to address the gap between insights and actions for merchandising and marketing decisioning.  Even a modest improvement in reduction of excess stock, out of stock or deep discounting will make a significant difference to a retailer’s bottom line.  It will create significantly more impact than any marketing campaign could.

At Acxiom, we know that the road to recovery for retail will have its challenges.  We’re harnessing the power of our customer intelligence solutions to address the foundational issues impacting the retail sector in innovative ways. Click below to watch a quick video.

If you’d like to learn more, please contact us at

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