V-SHOPPER is a virtual shopping test platform that uses REAL STORE SHELVES in a VIRTUAL SHOPPING ENVIRONMENT to confidently predict the BUSINESS IMPACT of different pack designs, advertising stimulus, and new products by measuring ACTUAL SHOPPER BEHAVIOUR at the moment-of-truth.

SHOPPER BEHAVIOUR MEASUREMENTS

1. What shoppers see while shopping

2. How quickly they can find a specific SKU

3. What shoppers purchase

WHY V-SHOPPER?

Only V-SHOPPER can accurately track shopper eye movement online.

The product SKU density of most store shelves requires a hyper-specific tracking mechanism that only V-SHOPPER has. We call it the Ocular Lens. It is like a zoom lens for shoppers to use while scanning the shelf and is controlled by their mouse. Our Ocular Lens is not only unique, its efficacy has been fully validated by third-party studies.

It’s really critical for brand owners to get accurate shopper attention data so that brand performance can be optimized – you can’t optimize what you don’t measure!

With the majority of purchase decisions still being made at the POP,  shelf impact is a competitive weapon that needs to be honed, along with purchase conversion, to grow market share and sales.

MEASURE, MEASURE AND MEASURE

MEASURE WHAT SHOPPERS NOTICE ON-SHELF

OCULAR LENS TRACKS EYE MOVEMENT THREE TIMES PER SECOND

Shoppers are asked to shop as they normally would and use V-SHOPPER’s proprietary Ocular Lens (like a magnifying glass) to navigate the shelf. The Ocular Lens places shoppers about 18” from the shelf and is controlled by their mouse.

We measure eye movement every third of a second throughout the shopping experience with the Ocular Lens.

Report Findings: How many shoppers, as a percentage, paid any attention to your brand on-shelf while shopping, and how does that compare to your competitors and other test variants.

MEASURE HOW QUICKLY SHOPPERS CAN FIND A SKU

FINDABILITY

Shoppers are asked to scan the virtual store shelf and find a specific brand SKU. They use the Ocular Lens to find the targeted SKU and confirm selection.

Findability is an important measure of both shelf impact and on-pack communication. It is really a starting point to measuring a brand’s in-store performance because you can’t afford to get it wrong, particularly if you have a large business and are looking to make a change.

Report Findings: How many seconds (on average) it takes to find a targeted brand SKU and what percentage of shoppers picked the correct SKU.

MEASURE WHAT SHOPPERS PURCHASE

PURCHASE CONVERSION

Shoppers are given the opportunity to click on any product they see on-shelf and make a decision on whether to purchase it or not.

Measuring actual purchase behaviour within the context of a shopping trip is the only way to get accurate data on expected business impact. Why? Fact is there is a very poor correlation between what consumers say and what they do. That is one of the reasons why over 85% of new products fail using traditional purchase intent measurements.

With V-SHOPPER, there is a .85 correlation between test results and real world results, so it is highly predictable. This virtual testing of different marketing stimulants allows brand owners to effectively manage risk and optimize business results.

Report Findings: What shoppers purchased, purchase conversion rate percentage and market share for all brands on-shelf, as well as test variants.

LISTEN TO WHAT SHOPPERS SAY

INTEREST & LIKABILITY

PACK ANALYZER

Using the V-SHOPPER’s Pack Analyzer, respondents are asked to pick out the 3 most interesting elements (to them) on the pack design or brand ad, rate it out of 10 and comment on it.

Every pack design or brand ad elicits a response from the target audience. In order to optimize this response, marketers need to better understand what the primary interest drivers are, along with their level of likability.

This feedback is particularly useful if the brand is underperforming in-store, as it gives clues as to why the brand is struggling at the “moment of truth”.

The key here is to use this data in combination with the shopping behaviour data because it helps answer the question: why did that test stimuli perform so poorly or so strongly?

Report Findings: Maps all design elements against interest level and score, as well as provides verbatim comments.

BRAND SENSIBILITY

Shoppers are asked to rate their perception of a brand against a list of targeted brand attributes. This rating method is sometimes replaced with forced preference format to compare more than one design head-to-head.

This is the last step in the research process. It’s important to do for two key reasons. First, there is a need to confirm whether the marketing stimulus effectively supports the brand communications strategy. In our experience brand owners are often surprised at respondent perceptions of test variants.

Secondly, the insights gained in this area can be cross-tabbed against shopping and pack analyzer results, to better understand what is behind key performance drivers.

Report Findings: Brand salience scores for all design variants, cross-tabbed with shopping data.

3 TESTS

POP Benchmark

  • Is your on-shelf presence at the point-of-purchase (POP) competitive? 
  • This test uncovers where your brand ranks among its competitive set on-shelf in terms of both shopper attention level and purchase conversion. Findability is also measured and compared to success norms.
  • The test is an excellent starting point to determining whether a package needs a redesign because it also uncovers pack design positive and negative perceptions.

New Pack Design

  • A new pack design has been developed, but how will it impact the brand at retail in terms of shopper attention, business impact and findability?
  • This test uncovers how your new pack design(s) will perform on-shelf versus the current design and competitive set. 
  • The test takes away the risk of the unknown so that you can prudently “open the gates” to bigger and better pack design ideas.

New Product

  • Will your new product succeed in-market?
  • The test measures both the level of shopper interest and actual shopper behaviour in-store. This is a vastly superior methodology versus traditional studies that just measure purchase intent.
  • It will accurately predict trial rate and market share with and without brand stimulus exposed before respondents shop. The test will also calculate the opportunity cost of limited in-store presence and provide a buyer profile “sweet spot”.

PREDICTABLE IN-MARKET

RESULTS

WHITE PAPER

A team of researchers from two different universities partnered with Kraft Foods, Canada, to test V-SHOPPER versus more traditional in-store testing methodologies. They wanted to determine whether this newer, more cost and time efficient online testing methodology could measure shopper behaviour and attention as well as more traditional and expensive in-store testing methodologies. They chose V-SHOPPER for this test because unlike other online testing solutions, only V-SHOPPER has an Ocular Lens feature, a highly effective means of tracking shopper attention online throughout the shopping experience.
Two identical tests were run across 5 food categories with 1172 respondents using V-SHOPPER and in-store shop-along methodologies. V-SHOPPER purchase behaviour was compared against in-store shop-along data. In addition, researchers compared online shopper attention data from V-SHOPPER with normative shopper attention data sourced from many in-store eye tracking studies, to determine the shopper attention efficacy of V-SHOPPER.
Results showed a very strong .85 correlation between purchase behaviour data generated through V-SHOPPER and in-store shop-alongs. Further, researchers concluded that V-SHOPPER’s Ocular Lens was able to demonstrate expected results in most cases versus what was expected based upon normative shopper attention data. Conclusion from the study was that V-SHOPPER is able to provide managers with a more cost and time efficient methodology to examine the actual impact of marketing actions intended to capture shopper’s attention at the retail shelf and to influence behaviour.

Journal of Food Products Marketing, 2016 - http://dx.doi.org/10.1080/10454446.2015.1072869Mark Lang, James Kelley, Kelly Moore (Department of Marketing, Iowa State University)