Winning the In-Store Purchase Decision Game: Five Critical Measures to Uncover Shopper Marketing Opportunities

Transcription

1 5 KEY MEASURES OF SHOPPER MARKETING OPPORTUNITY Page Winning the In-Store Purchase Decision Game: Five Critical Measures to Uncover Shopper Marketing Opportunities Written by, Lily Lev-Glick Principal, Shopper Sense As today s shoppers face an onslaught of choices in-store, what opportunities exist to improve category performance? Dating back to the 1950 s, the Point of Purchase Advertising Institute as it was then known, began to delve into purchase decision behavior and produced the POPAI Consumer Buying Habits Study. The insights at the time were groundbreaking as few, if any, companies were researching what was then considered below the line media. POPAI conducted the studies once a decade as the dynamics of shopping changed at a glacial pace in the opinion of most marketers. It was a world where channel blurring was unheard of, only three major TV networks existed and mobile marketing were ads on the sides of delivery trucks. As far back as 1988, POPAI s research revealed that two-thirds of purchase decisions were made in the store. In 1995, the measure bumped up to 70%. Today in 2012, the widely quoted in-store decision rate from POPAI s Shopper Engagement Study has reached an all time high of 76%. We all know that shoppers proclivities for finalizing purchase decisions in-store exist in a big way. But (I guess) it s even in a bigger way than expected given today s complex shopping landscape filled with multi-layered selling strategies, social media and shopper technology. It s all great news actually since the most notable shift within the in-store decision rate is the increase in the level of brand decision-making at the pointof-sale. More than ever before supermarket shoppers are choosing their brands in the store, after they explore a broader consideration set, and draw on store inputs to guide their final selections. For the shopper marketing industry this means more opportunity than ever before but also that more is at stake for brands and retailers. Each sku, in each category, on each shelf, and in each aisle is at the mercy of shopper distractions, abundant messages and a deselection process of filtering out products that barely get noticed in the first place. Some categories do better than others at winning the purchase decision game. They capitalize on shoppers high levels of impulsivity or the ease with which they are shopped. Other categories struggle as they fail to engage or inspire while floundering new product introductions and falling short of trading up their takers. Page 1

2 For these reasons alone marketing-at-retail needs to be as on point as ever. Many product groups continue to underperform amidst the challenges instore and are in immediate need of tools and tactics to better guide shoppers decisions, grow their categories, and increase share of basket among wallflower brands. POPAI s 2012 Shopper Engagement Study generated a vast, rich data set which is comprised of four sources: A census balanced sample of over 2,400 shopper interviews (geographically dispersed across 17 major US markets and 12 leading supermarket retailers that included Safeway, Stop and Shop, Vons and Winn Dixie among others), purchase receipts with over 33,000 items documented, eyemovement recordings and EEG data from 210 individual shopping trips, and an extensive audit of nearly 6,000 display units. 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 gleaned from the initiative, five distinct measures of category performance emerged. When amalgamated, these indicators become a compass for shopper marketing opportunity. This white paper identifies each of these measures, discusses the performance and opportunities among a sub-set of high volume categories, and examines what these performance metrics mean for shopper marketing strategy. Ease of Shopping Score (ESS) Based on a battery of attribute ratings, POPAI was able to compute an aggregate score that measures a category s performance on ease of shopping. The Ease of Shopping Score or ESS is reflective of overall category shopability. A high ESS indicates that the products are organized in a way that allows shoppers to easily assess the variety of options available to them and select items they need without difficulty. Shoppers do not find these categories confusing. Inspires Exploration Score (IES) Attribute ratings were also used by POPAI to compute an aggregate score that measures the degree to which a category inspires exploration. The Inspires Exploration Score or IES indicates how well a category s presentation encourages shoppers to spend time examining options on the shelf. Shoppers find it easy to discover new items in high IES categories In-Store Decision Rate The in-store decision rate is defined as the sum of three purchase decision types identified by a comparison between reported pre-store planned items and post shopping register receipts. It is a powerful barometer for measuring how deep the store environment, merchandising, promotions, packaging, and price penetrate category and brand decisions during the shopping trip. Five Measures of Category Performance 1. Ease of Shopping Score (ESS) 2. Inspires Exploration Score (ISS) 3. Category Conversion ( walk-away rates) 4. In-Store Decision Rates 5. Fixation Rates Page 2

3 The decision types include the following: Generally planned purchases a category was planned prior to the store but the specific brand was not 2. Substitute category or brand purchases - a specific category or brand was planned prior to the store but another category or brand was selected instead 3. Impulse purchases - an item that was not reported as planned either on a written, digital or mental list prior to the store but was purchased after the shopper entered the store. A fourth kind of decision, specifically planned purchases, is not part of the in-store decision rate but an important measure to mention. It reflects the rate in which specific brands were planned prior to the store and were in fact purchased exactly as intended. Categories that boast high specifically planned rates show in-store decision rates that are lower than average. Category Conversion ( walk-away rates) The POPAI study found that nearly six out of 10 shoppers failed to purchase at least one category item they planned on buying prior to entering the store, an indication that far from every planned category decision converts to a sale. The Category Conversion metric tells us the degree to which shoppers walk-away from planned transactions. Category Fixation Rates Eye-tracking fixation measures were sourced from 210 shopping trips. Category fixations indicate the extent to which shoppers examine products on shelf (a fixation equals 200 milliseconds). It correlates to the length of time shoppers dwell in a section which may or may not be for productive reasons. An extended dwell time may mean positive engagement or confusion. These measures must be looked at in concert with the other indicators explored herein. Where are the Category Opportunities? When looking across several high volume categories we see that some achieve success on a few measures while others do not hit on any. A few play several roles well and others only a singular role efficiently. It is important to consider the multiple dynamics of categories and to understand that where there may be an area of weakness there may also be an area of strength. Strategies must be conceptualized with both ends of the equation in mind. Marketers must think of the shopper-to-shelf moment as an experience stemming from these measured variables. High and Low ESS Categories Carbonated soft drinks captured the highest ESS score indicating that it is among the easiest of sections to shop. It also received one of the highest levels of eye fixations in the store. This combination sets the stage for a winning category performance. Other frequently to moderately purchased categories such as refrigerated juice/juice drinks, laundry products, cereal, crackers, and pet food also secured a high ESS. On the other end of the spectrum is candy, HBC, frozen foods and packaged cheese with the lowest ESS scores. Frozen, in fact, generated the highest eye fixation rates but when combined with a low ESS is a symptom of shopper difficulty. Packaged bread, salty snacks, cookies and paper goods demonstrated weak shopability levels as well. High and Low IES Categories Packaged sweet baked goods captured the top IES rank. Other hedonic categories such as cookies, frozen desserts, and salty snacks follow behind. Staples such as packaged bread and refrigerated juice/juice drink share the high IES podium with hedonic categories. And while pet food may be Page 3

4 considered easy to shop it falls lowest in rank for IES along with HBC items. Carbonated soft drinks, candy, crackers, frozen foods and laundry products also do not inspire exploration. High and Low In-Store Decision Categories A review of in-store decision rates reveals that candy, cookies, sweet baked goods, salad dressing and household cleaning top the list of high in-store decision rate products. While the former may be triggered more readily by impulse, the latter categories tend to capture a greater degree of brand consideration and switching at shelf as shoppers review prices and the available brand set. Laundry, carbonated soft drinks and pet are among some of the lower in-store decision rate categories. This may not be at all surprising given the repeat buying patterns for these products. Shoppers simply tend to pick up the same items they know work rather than take a risk. Low Conversion Categories (high walk-away ) When thinking about planned category purchases we expect that they will lead to a sale. However, that is not the case. Among high walk-away rate categories we find hedonic items such as sweet baked goods, ice cream, candy, cookies, potato chips and frozen desserts (they make up 25% of the top non-conversion categories). What is particularly interesting about sweet baked goods is that the category inspires a considerable number of impulse purchases (as discussed above) but there are many missed planned opportunities, the degree of which we previously may not have fully recognized. Other low conversion categories include household cleaning products, salad dressing and laundry products. Translating Insights Into Activation High ESS categories have solid foundations of shopability and findability and change must be carefully guided. High ESS scoring categories, especially when coupled with a high rate of eye fixations, indicate that shoppers heavily engage with the section, view many of the products on the shelf and do so with relative ease. Shoppers tend to find what they need among these sections that showcase variety well. However, these high performance categories are often driven by category familiarity due to frequent purchase cycles. Marketers must be cautions that shoppers are sensitive to shelf reconfigurations and other changes in these categories. Any alterations can result in confusion and the disenfranchisement of a core group of repeat purchasers. Such a dynamic may ultimately drive non-conversion in these frequently shopped and highly planned categories. Lower ranking ESS categories create difficulty and confusion for shoppers. They demand the greatest need for reworking shelf organization, enhancing product visibility and better planogram strategies. These sections are a threat to their products success. We often see high levels of eye fixations in these categories but they are due to unproductive dwell time and a marginal customer experience. These categories do not present variety well and choices are often lost in the clutter. A first step is to reevaluate these categories and determine how to better align the shelf architecture with shoppers needs and priorities in the category. Second, these categories tend to be displayed across large sections of 12 ft. or more. This perspective can be very difficult for shoppers to visually process or to feel grounded at. These configurations may benefit from a product segmentation approach Page 4

5 whereby sections are visually broken down into more manageable groups of 4-6ft. so that products can be better differentiated at shelf and streamlined for a more logical flow of product choices. Overall communication and messaging should be particularly direct, clear and visible in these categories so as to negate any confusion. Visual imagery often works well to better assist the shopper in navigating these product sets. 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. A high IES may be considered the crown jewel of shopability scores because these categories are best positioned to inspire trade-up, incremental purchases and introduce new products. Marketers should take a diagnostic look at the performance of high IES categories to understand what has worked well and then investigate ways to transfer the model to comparable categories that perform lower on this measure. A high IES score is only one part of the puzzle however. In the case of several previously mentioned categories (a few staple items and hedonic products) we see that despite positive IES performance there are a considerable number of planned purchases that are not consummated. In these instances high walk-away rates are less about category presentation and more likely attributable to an internal shopper cue that discourages followthrough (see low conversion discussed below). A low IES performing category creates risk for new product introductions and impedes trade-ups to higher margin skus because shoppers are less open to a shelf journey. Low IES categories indicate a need to better drive engagement and exploration. These categories may benefit from strategic and tactical activations that enhance the category s visual look. Category management approaches to optimizing the product assortment are vital as well. There is also great opportunity for leveraging point-of-purchase display, signage and packaging in these categories as well. New products or those that need to see a bump in sales, awareness or brand imagery may want to step out of the main selling area to encourage consideration when trapped in low IES groups. Marketers should look to capitalize on the shoppers emotional payoff from high impulse items. Lower in-store decision rate categories are habitually bought and they tend to capture a brand loyal shopper base. High in-store decision rate categories are comprised of a large impulse component. The study found that 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. Designs and messaging with an emotional component can easily be integrated into these display types. Low in-store decision rate categories do not easily convert buyers away from other competitive brands and they are destination categories for planned shoppers. Since endcaps play a strong way finding role for shoppers by acting as a beacon to the main selling area for planned categories they are a good choice for high planned/low impulse products. It is imperative however, that the gondola planogram (for the displayed end cap products) mirror that of the endcap so as to not create confusion at shelf or disrupt the shopper s flow as they seek the brand they are looking for in the aisle. Indulgent categories need an emotionally charged message to act as a tipping point for shopper follow-through. Hedonic categories such as ice cream/frozen desserts, cookies, and salty snacks (a high eye fixation category) perform well on the IES and are more frequently unplanned but they also show Page 5

6 notable walk-away levels. These products and other categories like them are laden with guilt and shoppers will often rescind their own pre-store permission to make this purchase by finding an excuse to not follow-through. Price is often used as an immediate dissuader as is an aisle with an overwhelming appearance. It is recommended that marketers engage strong tactics to draw on the intentions of planned shoppers in these categories by utilizing language and communication that resonate with the emotional reasons behind why they planned to purchase the category in the first place. Non-consumables tend to suffer from high walkaway" rates as a lower sense of urgency and price sensitivity give shoppers room to put off the purchase. These less glamorous categories often have an expansive sku selection with confusing shelf configurations and large product sets (i.e. laundry, cleaning products). They are not purchased as frequently at the supermarket channel so when supermarket shoppers plan to purchase them and they are not available at an acceptable price point shoppers walk away and wait to purchase them at a later time or at a different channel. Marketers need to take a close look at the lowest conversion categories and ensure that these departments perform well on shopability and findability, drive motivation for entering the aisle and provide enough price incentive to help drive planned category purchases that often take place at more competitively priced alternative channels. Marketers should also take steps to understand the impact of low conversion categories on adjacencies. Depending on shopper footprint, adjacencies of low conversion categories could suffer decreased traffic or from a negative halo effect. Where Do We Go From Here? 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. One of the most important steps marketers can take is to understand how their category performs in each of the five key performance measures discussed in this paper. When key stakeholders can isolate shopper pain points through these indicators they can then build strategy to rework the category and resolve unfavorable performance. While these five measures are not the only variables for a category s success they are fundamental components. Insights from POPAI s detailed category reports, which include data from interviews, EEG, and eyetracking, will deliver on these measures. I recommend using them along with other supplemental research (either secondary or custom) to develop targeted initiatives for each of the category opportunities discussed and others that warrant further exploration. 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. Page 6

7 Category Opportunities at a Glance Category Performance Measures CSD Candy Cookies Frozen Desserts Household Cleaning Laundry Sweet Baked Goods Refrigerated Juice/Drink Packaged Bread Salty Snack HBC Crackers Frozen Foods Salad Dressing Low IES, High ESS, High Fixations High walk-away rate, Low IES, Low ESS, High IDR, High Fixations High walk-away rate, High IES, Low ESS, High IDR High walk-away rate, High IES, High Fixations High walk-away rate, High IDR High walk-away rate, Low IES, High ESS, Low IDR High walk-away rate, High IES, High IDR High IES, High ESS High IES, Low ESS High walk-away rate, High IES, High Fixations Low IES, Low ESS Low IES, High ESS Low IES, Low ESS, High Fixations High walk-away rate, High IDR About the author: 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. POPAI s 1995 Consumer Buying Habits Study was conducted under Lily s direction while she served as Director of Research for the organization. Most recently she was engaged by POPAI to oversee the 2012 Shopper Engagement Study. The convergence of her industry experience has led to her recognition as one of the most skilled strategists in the field of shopper insights. She is the Principal of Shopper Sense, a shopper insights consultancy located in New Jersey. Lily can be reached at lily@shopper-sense.com or Shopper Sense LLC. All rights reserved. Use and distribution limited solely to authorized personnel. The use, disclosure, reproduction, modification, transfer, or transmittal of this work for any purpose in any form or by any means without written permission of Shopper Sense LLC is strictly prohibited. Page 7