Last month, we discovered that artificial intelligence, far from being a threat to retail marketing teams, is, in fact, an essential team player. The early results of using DecaSIM’s AI tools in conjunction with Comosoft LAGO showed that the two systems complement one another, each providing unique benefits for retail advertising and marketing directors. In this month’s article, we look at the two companies’ plans and what they mean for retailers of every kind.

Test overview

Recently, we tested the effect of using AI to optimize product selection in a regional grocery chain’s marketing campaigns. As reported in the published case study, the results were truly remarkable.

In the test, the regional grocery chain selected a 104-store region (out of over 300 stores) and, using Comosoft LAGO, created a specific version of its weekly ad circular to optimize during the test period. Each week’s promotional plan was run through DecaSIM’s AI optimizer during the test period. The analysis results were used to select which items to feature on each page of the circular. Compared with the sixty-five other stores chosen as a control group, the AI-assisted promotions increased sales by over $4,000 per store per week.

As AI improves profitability in the retail grocery sector, other retail chains can expect similar or even better results.

The importance of foot traffic

DecaSIM co-founder Doug Edmonds described a crucial factor in the grocery retail industry that is common to all retailers.

“All retail is trying to drive foot traffic, often with price as an incentive,” he said. “Whether you’re a grocery business or a home improvement retailer, if you depend solely on infrequent shoppers, you won’t survive.”

Edmonds continued, “Every retailer has a ‘core shopper group’ they must satisfy. Whether they’re buying tomatoes or socket wrenches doesn’t matter; their product preferences, shopping habits, and price sensitivity matter. Using AI to learn those things gives all retailers an edge. It will help them sell more to that core group. It will also grow that regular foot traffic over the long term.”

Comosoft’s US President Randy Evans noted that the grocery industry was only the beginning. “Grocery retailers have been using LAGO for years,” he said, “especially those chains that require regional versions of their weekly flyers and mobile shopping apps. We’ve always made it easy to prioritize offers, pull data from various sources, and streamline the design process across multiple stores. A fast turnaround is essential. But with DecaSIM’s AI tools, grocery advertising and marketing directors can know what products to prioritize in each campaign. It’s a slam dunk for our grocery clients, but our other retail clients can do the same thing.”

Diamonds in the rough

This use of artificial intelligence solves a problem facing all retailers—finding meaningful information in a mountain of product data. With thousands or even millions of individual products from many sources, retailers’ databases today are jammed with data related to each SKU. Typically, these reside in product information management (PIM), digital asset management (DAM), inventory, pricing, and marketing management databases. Too often, they are poorly integrated, forcing marketing heads and designers alike to hunt for detailed information for each product. This process is both time-consuming and prone to costly errors. With limited time and a seemingly unlimited array of print and digital channels, picking which products to feature involves a combination of intuition and guesswork.

LAGO’s unique ability to unify the PIM, DAM, and other data sources is part of the solution, creating a collaborative workflow, including both the design and the review and approval process. But even with a data-optimised, multichannel workflow, it still falls to the advertising and marketing directors to make priority decisions during the planning process. And even experienced planners may miss promotional opportunities amidst all that data.

Enter the AI part of the equation. DecaSIM’s artificial intelligence tools take data from each previous LAGO-driven campaign, identify patterns of core shoppers’ product preferences, and derive inferences and purchasing patterns, faster and with greater accuracy from that mountain of data. It then returns the results to LAGO, in effect “supercharging” the metadata used to create multiple versioned campaigns. AI can, in effect, find marketing diamonds amid raw data that would take humans too long to process.

Roadmap to marketing success

Comosoft Product Manager Steve May outlined what this could mean for future versions of LAGO.

“Today, campaign planners use our whiteboarding feature to create offers and product groupings that make the most sense based on margin, availability, and success in previous campaigns,” he said. “LAGO could add AI-generated weighted scores, relationships to other products, seasonal or regional patterns, and other useful indicators to featured products. They would still choose which ones to use but would be more informed marketing choices.”

By adding AI to LAGO, sales and marketing campaigns could be planned and executed at scale, with an objective knowledge of their sales potential. Far from taking jobs away from retail marketing professionals, AI would serve as a highly efficient research assistant, gathering objectively valuable information that the planner would use to create effective campaigns.

“Today, people are nervous about AI and what it will do to their careers,” Evans said. “In the case of retail marketing, it’s pretty obvious that AI is an ally in our data-intensive world.”