Why do grocery retailers still do promotion planning (price/item) around antiquated weekly circular planning routines?
There would be little debate from grocery merchandising, sales, pricing and marketing colleagues that ad planning is the most time consuming and essential task in a grocery retailers daily life to drive sales. The process encompasses the often antiquated and necessarily accelerated tasks of combing prior year and competitor ads, promotion histories, price books, current market/competitor conditions and syndicated seasonality data to assemble a single weekly ad plan to motivate a consumer shopping decisions.
Historical circular ad planning was intended to "win the shopping trip" that week. Not long ago were the days of consumers pulling weekly printed flyers from newspapers and laying them out on counters to compare and contrast front page flyer offers. The prevailing merchandising strategy was generally loss leaders in center store, hot meat pricing on (hopefully) the most relevant and competitive cut or commodity, plus the lowest priced produce truckload item based on market conditions. Salty snacks, carbonated beverages and orange-bottled laundry detergent were the ad equivalents of varsity quarterbacks.
Fast forward now to a retail grocery environment that is more competitive, differentiated and omni-channel than ever before. Consumers have real-time access to dynamic pricing across multiple online marketplaces, with the option to transact more dynamically, in real time and on demand. Given these paradigm changes, why do grocery retail merchandising teams still do promotional weekly planning around the old school weekly ad planning paradigm?
In any one week, teams are building up to four different detailed price/item weekly ad promotion plans; the ad about to release "to print", generally 2.5-3 weeks from sale date; the preceding weeks ad promotion plan in its 1st or 2nd iteration, and the beginnings of the ad preceding that one. In parallel the "shell" plan with category placeholders is built for the current month and quarter, with burdensome day blocks on calendars for the next Quarter ad planning session. The scurry is real, as merchandising teams shift items due to market changes, product shortages, competitor prices and late breaking commodity availability.
What if grocery retailers could plan promotions dynamically, meeting consumers where they are in their buying journey based on real-time consumer demand indicators? What if competitor price scraping was real-time, with algorithms smart enough to reprice based on in-stock positions, consumer demand, placement in-store (and if it was promoted previously) and impact to the potential full basket and total store sales? Most commercial pricing tools consider macro history in their algorithms but real-time, predictive consumer-centric promotion pricing still evades, as does dynamic pricing at the consumer level.
Given these macro limitations, a practical alternative to latent, outdated weekly ad planning paradigms is "halo-based" promotion planning. This methodology considers the impact of an items potential and likelihood to impact the purchase of another complimentary item(s). This approach shifts merchandising teams decision-processes from rigid historical data and weak vendor-funded offers to consumer-centric, sales building opportunities. Grocery retail organizations still must operate within the weekly ad planning paradigms, as these methods support essential sales-building business functions from ordering, deliveries, in-store merchandising, holiday planning, campaigns, vendor deal flow management and more.
The best future tools will leverage Native-AI to help retailers calculate high halo sales potential based on offer type, placement, depth of discount, seasonality, holidays and recency/frequency, plus marketing campaign, channel and sale duration. These predictive outputs are not computationally impossible today - they are just unavailable to most retail merchants and marketers given time crunches, lack of data access and analytic horsepower and the constraint of category-centric promotion planning (vs a total store approach).
What if retailers could calculate high halo total sales potential item plans for an entire year (52 weeks) based on a scrape and analysis of 18-24 months of sales history? This is entirely possible today - without SaaS contracts, endless roadmaps, needless data mapping and tone-deafness to how grocers go to market. This is also entirely possible, while delivering incremental top line sales, total margin enhancement and increased transactions.
#promotionintelligence #nativeAI #groceryretail #adplanning #promotionplanning
