Nimbus is being launched in an extremely dynamic marketplace with no clear antecedents to show the way because it represents a totally new market research capability. It represents, we feel, an opportunity to define itself in terms of what the market is looking for rather than a replacement for conventional eye tracking which has only limited applications in package design and shelf arrangement.
Nimbus represents the first in a new breed of market research tool that delves into the complex decision process that represents the purchase decision. Since it is commonly believed that 70% of the factors influencing consumer purchase decisions are in-store, we feel that Nimbus can be positioned as a critical resource within the consumer packaged goods industry. The target audience consists of middle level and top level managers who practice the principles of category management within the packaged goods industry.
As Professor Ted Leavitt of the Harvard Business School said, “People don’t buy ¼ inch drill bits, they buy ¼ inch holes.” Integrated eye tracking and virtual shopping is the ¼ inch drill bit and we are looking for what constitutes the ¼ inch holes that potential clients really want.
The launch of Nimbus coincides with a growing need on the part of category management to embrace new methods of measuring and predicting consumer demand for packaged goods. In order to accomplish that objective we have to take a detailed look at what the consumer packaged goods industry is really looking for.
CPG Companies and retailers are implementing category plans based on a shopper-centric point of view – one based on need states/shopping occasions as opposed to traditional customer segmentation views. The innovating companies are moving dollars away from merchandising and channel-specific marketing to efforts to influence consumer shopping and purchase behavior, marketing is now becoming more customer analytics driven and at the same time customers are becoming increasingly wary and more difficult to predict. Analysis of need states (why shoppers choose what they choose and what they tend to choose in a particular state of mind) is very important in order to remain in top competitive form.
A shifting value proposition and changing industry dynamics have led to micro-merchandising as the tool to enable customer centricity:
- Micro assortment planning – tailoring assortment to stores or store clusters
- Granular pricing and price optimization
- Customization of promotion and promo display space
- Macro and micro-space planning (customize store layouts and planograms down to individual clusters)
The retail store is still the primary battleground for the shopper’s wallet. Even with the continued evolution of online marketing, the accepted wisdom that 70% of the consumer purchase decision is made in the store is still true. Furthermore, with nearly 68% of in-store purchase being impulse the opportunities to reach consumers and stimulate increased consumption with improved shelf management, POS promotions and package redesigns are boundless. Marketing to shoppers within the store environment is more focused and more efficient than standard mass advertising particularly at a time when consumers are feeling pinched by the economy.
The key to improving shopper marketing in the store lies in understanding the motivating stimuli that evoke the purchase. Since no two shoppers are alike, the relative importance of shelf position, price promotion, eco-friendly labeling and package design varies from shopper to shopper and indeed from trip to trip even for the same shopper. Nimbus measures the impact of these stimuli on individual shoppers therefore:
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Nimbus is uniquely positioned to provide greater insights into shopper marketing at a time when that is recognized as a strategic objective. |
Pantry restocking or grab ’n go evoke two totally different opportunities. Often the shopper is not buying the product for themselves but choosing it for a different member of the household who is the end consumer. These are just some of the complications to “getting it right”. In other words, if you knew why the shopper was in the store and who they were you could put your most effective strategies in play to win the purchase for your brand. Wouldn’t it be nice if there were a single source for getting all of the inside scoop on the shopper. Well, now there is! Nimbus is a totally new market research tool that breaks new ground in being able to delve deeper into the purchase decisions within a controlled store environment that allows testing of multiple stimuli at the same time within the context of a given shopping trip.
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Nimbus allows the study to be configured to echo the different types of shopping trips that are becoming more common. |
By delving in depth into the influence of stimuli that impact the final purchase decision, Nimbus is providing the marketer with the tools to implement shopper-centric marketing – that is satisfying shoppers’ need-states. This is nothing more than marketing to consumers when they are in the shopping mindset to satisfy the need that drove them to the store. The shopper does not care whether the marketing stimulus they are receiving is an advertisement, consumer promotion, trade promotion, product package, or store placement.
Some examples of shopper marketing stimuli include:
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Product stimuli, such as the size, shape, color, material and packaging of the product, and the messages, graphics and language conveyed on the packaging
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Price stimuli, such as price promotions conveyed in circulars, shelf signs, coupon dispensers, and personalized check-out coupons
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Place stimuli, such as store design, layout, lighting, music, scents, and aisle, shelf, and display locations
- Promotion stimuli, such as sampling, demonstrations, displays, floor advertisements, kiosks, in-store visual or audio, intelligent shopping carts, and digital signage.
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Nimbus puts the virtual shopper into the driver’s seat in terms of responding to stimuli through both their eye gaze as well as their hands via a joystick. This mimics the real life shopping experience and provides a shopper-centric marketing decision support tool. |
The retailer provides key manufacturers with scan data including category and brand volume. Third party vendors conduct in-store observation studies across all channels and markets, providing manufacturers and retailers with visually verified information about categories, brands, items, retail execution and the competition.
Data syndicators conduct panel studies and overlay demographics on purchase behavior. Nielsen offers the industry’s best longitudinal panel with the broadest sample size to deliver deep and granular insights into consumer purchasing behavior. Now providing key consumer insights in 28 countries based on consumer purchase information from over 300,000 households globally
For example, ACNielsen’s comprehensive data suite permits management to examine key business trends by product, category, store, chain, or market for one brand or an entire competitive set across the food, household, health and beauty, durables, confectionery and beverage products industries. From viewing an executive summary to drilling down through a robust database to the desired level of detail, executives can make strategic decisions based on accurate, timely information.
Finally, the manufacturer has its own inventory, product movement, brand market share, distribution, price and other market-sensitive information.
One problem that arises from these separate data sources is that the data isn’t synchronized. Data series are not completely comparable across sources and there are different assumptions that need to be made to make data projections consistent across sources. This is particularly problematic as category management plans are calculated through the employment of large integrated spreadsheets that import data directly from the sources. Building a set of category management goals that are internally consistent is a major activity of the support staff. When there is a major change in the competitive space, these projections need to be recast in order to project consumer demand accurately. Often it is a matter of only days before the category management plan becomes obsolete and new tactical objectives become necessary.
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There is an unmet need for a source of synchronized data that can reliably be used as input into Category Management Spreadsheets to drive projections. This need is filled by Nimbus. |
A second problem is that in-store metrics is still sketchy. This is being addressed by an industry consortium that has recently announced the results of its pilot in the U.S. This is described in the next section.
The PRISM Project: Pioneering Research for an In-Store Metric is the retail industry's most significant initiative to establish a global metric for evaluating the in-store environment as a marketing medium along the lines of Nielsen's TV, Internet, Box Office and other audience metrics. Understanding the store environment is critical as seventy percent of all final purchase decisions are made at the shelf. For the first time, the P.R.I.S.M. Project allows in-store traffic to be measured by product category, such as in the cereal aisle of a food retailer or in the hair care aisle of a drug store.
- Traffic and Sales - P.R.I.S.M. shows that category transactions alone are not a reliable indicator of category traffic, counter to conventional wisdom. Two-thirds of shoppers who visit the salty snacks section in a food store make a purchase. Traffic is far heavier past the dairy case but the "closure rate," or number of shoppers who make a purchase, is much lower for dairy products.
- Demographics - Only 13 percent of food shopping trips are with kids, but P.R.I.S.M. data shows shoppers put more in their baskets overall when children are with them. This dynamic is constant throughout the week and across most top product categories, including hair care and water. Seasonal items are two and a half times more likely to be purchased when kids are present. Interestingly, the presence of kids on the shopping trip has little impact on candy sales.
- Marketing Influences - Shoppers are communicated with frequently in stores: the average number of individual pieces of marketing stimuli in a grocery store is about 3,500 and larger store formats, such as mass merchandisers, have over 5,000 stimuli. A typical drug store has roughly 2,300 individual pieces of marketing stimuli.
David Calhoun, Chairman and Chief Executive Officer, The Nielsen Company, said: "Industry-accepted metrics typically emerge because of need. It's how Nielsen's television ratings became indispensable to understanding viewership and it's how the Internet has gone from an undefined medium to a measured platform... There's too much money at stake for the in-store experience to be left to intuition."
Steve Bratspies, Senior Vice President of Marketing, Wal-Mart Stores Inc., added: "The richness of P.R.I.S.M. data will complement our years of expertise to help us better understand what is working and what isn't for our customers. It can dramatically change the way we as retailers create a more compelling in-store environment by helping us to truly anticipate the needs of our customers. I believe the greatest benefit of this project will be fundamentally improving the shopping experience."
Sandy Douglas, President and Chief Operating Officer, Coca-Cola North America, said: "While we use a wide variety of marketing vehicles, we know that the vast majority of shopping decisions are made at the shelf. P.R.I.S.M. will create more insightful analytical tools to help us connect with shoppers in a more effective way."
Bob McDonald, Chief Operating Officer, The Procter & Gamble Co., said: "Winning at the shelf is about truly understanding what shoppers need to know and how they like to shop. Ultimately, nothing matters unless we can delight the shopper and P.R.I.S.M. is going to help us deliver that experience every time."
Renetta McCann, Chief Executive Officer, Starcom MediaVest Group, said: "By mapping store traffic and enhancing it with consumer feedback and compliance measures, we will have a much clearer, more measurable and predictable grasp of what the consumer is going to do inside a store. That absolutely changes the conversations we will be able to have with our clients as we map out the touchpoints that propel a consumer from intent to response."
Peter Hoyt, Executive Director of the In-Store Marketing Institute, said: "The P.R.I.S.M. findings will change the way manufacturers, retailers and agencies view the in-store environment. It confirms that in-store consumer reach can be measured and predicted with great reliability, which will enable marketers to enhance the efficiency and quality of the shopper's experience."
Yet despite these glowing words from the supporters of the P.R.I.S.M. initiative, the blatant truth is that there are no data sources that address the issue of how the shopper makes that final critical purchase decision. This missing piece of information creates a perfect position for Nimbus.
Most consumers shop on auto-pilot. Underlying repetitive purchase patterns are a set of cognitive decision rules – the ‘programme’ behind ‘auto-pilot’ purchasing. These are called Omega Rules – the mental check-lists that keep consumers on-track and help them decide between alternatives. Often these rules are quite mundane (e.g., pack shape) or social (e.g., acceptable to friends) and do not represent deep emotional commitment to the brand. Brand leaders must understand Omega Rules as they provide guidance on key marketing tactics that will reinforce the habits that give them leadership.
As distinct from auto-pilot mode shopping, marketers identify the “Delta Moments” - those inflection points that offer the maximum opportunity for informed decision makers to build mind share and brand potential. During these Delta Moments consumers are most susceptible to try new products and engage in brand switching. Recent research indicates that consumers are far less brand loyal than thought and so it may be that shoppers are simply more inconsistent in their shopping than either Omega or Delta practitioners assume.
Most current brand research focuses on two areas:
- Measuring and mapping feelings and motivations of consumers about brands; and
- Measuring and charting consumer behavior and brand sales.
Nimbus blurs the distinction between these two research areas. Nimbus certainly measures behavior and sales with regard to a brand, however, in place of feelings and motivations Nimbus uses the eye gaze as a more reliable psychobiological measure of pre-buying interest and intent.
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Nimbus utilizes more reliable psychometrics to analyze pre-purchase interest and motivations. |
In a recent study completed before the dramatic increase in gasoline prices, 73 percent of shoppers were found to patronize five or more channels. This percentage has dropped dramatically with the rise in gas and the slowdown in the economy. Witness the improved quarterly financial results reported by deep discount retailers like Big Lots or the increased revenues at giants like Wal-Mart. Shoppers are pursuing a strategy of consolidating their shopping trips and targeting deep discount retailers for shopper forays. This phenomenon is called “Channel Collapse” and is one of the most striking challenges to manufacturers and retailers alike today.
Channel collapse is both a threat and an opportunity to the CPG’s industry. As more shoppers are seeking to fill their shopping needs in unfamiliar environments and thus are more susceptible to brand switching or even switching retailers. The development of more effective in-store strategies will reward the innovating retailer disproportionately. Since major CPG companies act as category captains, it becomes their responsibility to address the issue of channel collapse as well.
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Nimbus can be used to measure the extent of this collapse and to respond to that collapse proactively particularly with the retailer because of its field portability and ability to configure different store environments. |
Nimbus’ dynamic eye tracking and virtual shopping system uses the eye gaze as a portal to the consumers’ conscious thought processes as shoppers maneuver down the grocery aisle and consider buying products from the shelf.
Since as much as 70% of the decision process is thought to occur in the store and in front of the shelf, Nimbus is capturing all of the subtle eye movements that occur when that decision making process is unfolding. The eye may be attracted by a POS sign before focusing on the product facing. Then the shopper’s gaze falls on the price before going back to the product again. The product may be picked up and examined more closely. Then it may be put in the shopping basket or returned to the shelf. These eye movements taken together provide critical clues as to how the purchase decision is arrived at.
Through deep pattern analyses, Nimbus identifies different types of shoppers’ needs and interprets which of the multiple stimuli are most effective in eliciting brand purchase. This interpretive eye tracking delivers real value to increasing category volume and optimizing the use of marketing dollars.
Nimbus interpretive eye tracking has captured a wide range of gaze tracks through our field research:
Spontaneous Gaze Tracks – occurs when the shopper views the aisle without any specific task in mind. The gaze pattern is controlled by patterns such as novelty, complexity, incongruity where there is a lot of information content that needs to be examined.
Task-relevant Gaze Tracks – observed when the shopper has a particular task or end-goal. Thus, the shopper is seeking information of a special kind and the eye gaze pattern is affected.
Preoccupied Gaze Tracks – occurs when shoppers are not paying much attention to where they are looking but is attending to some “inner thought” or when other members of the shopper’s family are present.
Manipulatory Gaze Track – becomes operative when the shopper looking is looking at a specific item on the shelf with the intention of manipulating it. The subject is now more than a passive observer but interacts with the virtual environment.
Taken by itself a person’s gaze can be directly analyzed using conventional eye tracking metrics. The path of the gaze indicates where the points of interest are while the dwell time indicates the level of interest. These metrics are both useful and revealing by 1) helping designers improve product packaging, 2) guiding the design of a more successful planograms, or 3) identifying which POS signs are more effective. When multiple gaze tracks are analyzed even more information is available. One of the most useful techniques utilizes the same technology used to analyze DNA sequences – sequential pattern analysis.
Sequential pattern analysis retains the temporal nature of the gaze track and overlays the observed behavior. Did the shopper pick up the product after seeing the shelf advertisement? How influential was price in the ultimate decision to purchase the product or return it to the shelf? Did the shopper compare multiple products in the same category? Nimbus recreates the real shopping experience in a virtual world that allows these questions as well as many others to be answered. The benefit to category management is a marketing decision tool that gives precise metrics on multiple issues facing managers who have to respond to dynamic changes in the marketplace.
To help provide category managers with nearly real time answers, we first establish a baseline study using Nimbus. This study serves to synchronize the Nimbus output to volumetric data derived from traditional data streams such as scan data from retailers or syndicated panel data. We have taken a close look at some of the latest survey data that is coming on stream, including PRISM, and have positioned Nimbus as the marketing decision tool that completes the circle of knowledge around the shopper purchase decision process.
These more traditional sources provide inventory and movement data by category and individual SKU. Syndicated panel studies provide market basket analysis for shopper segments as defined by demographics or lifestyle. PRISM adds a new component for in-store metrics by measuring shopper traffic as people move down an aisle and past the category in a store where this system is enabled. Even with the latest advances, none of these data sources however reveals how or why the consumer makes that final purchase decision, which is precisely what Nimbus is designed to discover.
The baseline study employs the current planograms that are in place within the retail environment being studied. A Nimbus panel that is representative of shoppers for that retail environment (channel, geographic coverage, and retailer positioning) is recruited. Pricing levels and other promotional activities are set under steady state assumptions. Within a specific retail environment, about 400 respondents are adequate to establish a reliable baseline. The output from the Nimbus study is synchronized with the independently derived volumetric data coming from the retailer’s own scan data. A further refinement includes synchronizing the data for individual shopper segments, this might require a 50% increase in sample size.
The reason that interpretive eye tracking can be so revealing of the shopper’s decision making process is due to the fine granularity of the data. This granularity goes well below the interaction of the shopper with the SKU. It goes down to the interactions of gaze falling on price, manipulation of the item, reading of the label and other revealing behavior that is captured in a single integrated data stream for that virtual shopper. This granularity echoes the granularity evidenced in the real world and therefore provides robust support for the pattern analysis that reveals the very fundamental consumer thinking at that critical juncture when the shopper is standing in front of the aisle and considering purchasing a specific item.
The data includes the shopper ID, SKU, POV of the shopping trip, shopping environment including shelf arrangement and facings and various combinations of shopper controlled behavior that include viewing ad, viewing price tag, viewing POS, examining product more closely, reading back of label, putting the product back on the shelf, taking the product off the shelf again, looking at a competitive product in the same category, placing the product in the shopping basket, removing the product from the shopping basket and finally going through the check-out line.