NeuroRelay

Shopper Sense (a shopper insights consultancy located in New Jersey) recently released the whitepaper called “Winning the In-Store Purchase Decision Game: Five Critical Measures to Uncover Shopper Marketing Opportunities” writen by Lily Lev-Glick (Principal at Shopper Sense). For more than two decades, Lily Lev-Glick has researched, explored and analyzed shopper behavior, purchase motivations and how retail environments impact decision-making. During this time she has worked with brands, retailers, industry associations, shopper marketing agencies and point-of-purchase display companies to help them better understand category dynamics and shopper behaviors.
In order to read the document, provide here the information asked in order to receive it by email. This white paper identifies each of the indicators that become a compass for shopper marketing opportunity, discusses the performance and opportunities among a sub-set of high volume categories, and examines what these performance metrics mean for shopper marketing strategy.

POPAI’s 2012 Shopper Engagement Study generated a vast, rich data set out of a sample of over 2,400 shopper interviews (geographically dispersed across 17 major US markets and 12 leading supermarket retailers), purchase receipts with over 33,000 items documented, eye-movement recordings and EEG data from 210 individual shopping trips, and an extensive audit of nearly 6,000 display units. As Lily Lev-Glick says, this expansive, integrated research design resulted in the largest, most authoritative study of in-store purchase dynamics ever undertaken.
Among the numerous data and insights gained from this initiative, 5 measures of category performance emerged:
1. Ease of Shopping Score (ESS) reflecting the overall category shopability.
2. Inspires Exploration Score (IES) indicated how well a category’s presentation encourages shoppers to spend time examining options on the shelf.
3. Category Conversion (“walk-away” rates) the degree to which shoppers “walk-away” from planned transactions (according to the study, 6 out of 10 shoppers failed to purchase at least one category item they planned on buying prior to entering the store).
4. In-Store Decision Rates shows how deep the store environment, merchandising, promotions, packaging, and price penetrate category and brand decisions during the shopping trip (analyzing generally planned purchases, substitute category or brand purchases and impulse purchases).
5. Fixation Rates indicate the extent to which shoppers examine products on shelf (a fixation equals 200 milliseconds).

The analysis goes further by identifying the products for each category value:
High ESS Categories – carbonated soft drinks, refrigerated juice/juice drinks, laundry products, cereal, crackers, and pet food
Low ESS Categories – candies, HBC, frozen foods and packaged cheese, packaged bread, salty snacks, cookies and paper goods
High level of eye fixations – carbonated soft drinks, frozen foods
High IES Categories – packaged sweet baked goods, cookies, frozen desserts, salty snacks, packaged bread and refrigerated juice/juice drink
Low IES Categories – pet food, carbonated soft drinks, candy, crackers, frozen foods and laundry products
High In-Store Decision Categories – candy, cookies, sweet baked goods, salad dressing, household cleaning
Low In-Store Decision Categories – laundry, carbonated soft drinks and pet food
Low Conversion Categories (high “walk-away”) – sweet baked goods, ice cream, candy, cookies, potato chips, frozen desserts, household cleaning products, salad dressing, laundry products.

Integrate findings for marketers:
High EES + High level of eye fixations = the easiest of sections to shop; shoppers heavily engage with the section; driven by category familiarity due to frequent purchase cycles
Low EES + High level of eye fixations = symptom of shopper difficulty and confusion; they demand the greatest need for reworking shelf organization, enhancing product visibility and better planogram strategies; threat to their products’ success
High In-Store Decision Categories = large impulse; floorstands and power wings tend to facilitate consideration of unplanned items and therefore these may be more viable display choices for products that fall into a high impulse category group.
Low In-Store Decision Categories = repeat buying patterns for these products; do not easily convert buyers away from other competitive brands and they are destination categories for planned shoppers
High IES Categories = do the best job of encouraging shoppers to look at all of the items in the section and discover new or interesting products; best shopability scores; these categories are best positioned to inspire trade-up, incremental purchases and introduce new products
Low IES Categories = indicate a need to better drive engagement and exploration; creates risk for new product introductions and impedes trade-ups to higher margin skus because shoppers are less open to a shelf journey
High “walk-away” rates = non-consumables tend to suffer from  as a lower sense of urgency and price sensitivity give shoppers room to put off the purchase; confusing shelf configurations and large product sets (i.e. laundry, cleaning products).

Category opportunities at a glance – Copyright courtesy of Shopper Sense

As Lily Lev-Glick states, this white paper has identified several categories that can largely benefit from strategic in-store initiatives along with a general understanding of why and how (how their category performs in each of the five key performance measures discussed). Such insights can form the basis of tactical executions that optimize the use of visual imagery, color, messaging, display, and signage to effectively engage shoppers and ultimately elevate the performance of any recessive category.