5 Research Methods Proving the Value in Virtual

Posted by Rich Scamehorn on April 9, 2018

Virtual reality product
This article was originally published on LinkedIn by Rich Scamehorn.

The disruption and evolution happening to retail right now reaches far and wide. Nearly every aspect of the industry is undergoing some sort of transformation—and that includes the various methods used to gain insight into shopper needs and wants at the shelf.

As stores become more experience-focused and retail gets better at balancing the digital and physical spaces to better mirror the way people shop, market researchers need to innovate the way they learn about their shopper, store and product data. We’ve moved beyond purchase intent, you guys. Mixed reality technology is making it faster and easier than ever to gain deeper, actionable insights into the shopper mindset. The following are five common methods of market research that you’re likely familiar with, and the reasons why they need a virtual upgrade, right now:   

Shopper Decision Trees
Shopper/Consumer decision tree outputAnalyzing consumer decision trees are important for strategic and tactical decisions—they serve as a foundational research approach to help teams learn what aspects and elements of a shopping trip influence various purchase decisions. Traditionally, they are created either from historical purchase data (household panel data, for example) or attitudinal surveys. 

The thing is, we know historical and purchase intent data is inherently unreliable for predicting what shoppers will actually do. Today, virtual simulations offer a way to observe shoppers’ switching their behavior directly, and use this to create a shopper decision tree by retailer or region, before implementing changes in-store. We can also understand shoppers’ decisions for categories that are immediately consumed, that don’t have UPC codes, or that are purchased infrequently—all of which traditional methods struggle to address. Leveraging virtual helps your team learn how shoppers think about the category in real-time, and how that might vary across retailers and channels.

**Bonus: 4 Red Flags to Watch for When Developing Consumer Decision Trees**

Display & Signage Testing
Any concept that can be executed in a store itself can be tested using virtual. New ideas are often assessed using a mock center, such as displays and signage. But technology is allowing today’s market researchers to bypass the mock center step, and instead observe how concepts resonate with shoppers in the context of a virtual store.

visualize in-store displays in virtualFor example, our ShopperMX™ platform can help capture purchase data and shopper attitudes toward new signage concepts in the context of the store, or help measure the impact of your secondary product displays. Test shoppers feel like they are actually in a retail environment, making them prime candidates to understanding what works and what doesn’t, faster than ever before. 

This approach has been shown to provide sales data that is highly correlated with actual store sales, without having to build out and stock the mock store shelves. The digital approach can save time and money to understand which concept version most drives sales lift. 

Package Design

virtual product designOne of the most commonly used tools for brand impact is packaging, and we all know how fast a package redesign can go south. To avoid a design disaster at launch, it’s important to have realistic, in-context testing strategies in place to truly understand the impression new packaging will leave with shoppers. 

Virtual package testing methodologies allow teams to visualize how new graphics, colors, designs or messaging will look, and then further test the various concepts directly with real shoppers. Results are tied to sales impact, so you’ll know which packaging ideas are a hit, or which might be a flop—all before sending anything to production. Crisis averted. 

Location & Arrangement Optimization
color blocking on shelfShould a new product be placed within the brand block, or should it sit on the shelf with other similar-form products? Does a different placement within the planogram provide more exposure to a slower moving product and drive greater sales? 

Location on the shelf is important, yet product placement is often determined based on gut instinct. Virtual A-B testing helps break that cycle, providing accurate, timely data that helps you understand how shoppers will view different shelf options, from each of their unique perspectives. 

Price Evaluation
Price—including sales and promotions—is a huge factor in how people shop. But, it’s not the only factor. That’s why pricing testing is often an integral part of the go-to-market process. What will the impact be if we move our product over a price threshold? What is the elasticity for the price of a new product? What is the best multiples deal to offer, or should it be a lower everyday low price? Virtual research helps brands and retailers quickly find the answers to these questions. 

Test shoppers can complete various virtual exercises, each with different price points for the test product or category—but because their decisions are being made within a hyper-realistic virtual store (instead of seeing them on a survey, for example) their actions are more likely to mirror real life. They might think they would go for the lowest-priced item, but seeing it next to another item that has more enticing packaging might sway their decision. In virtual there is no limit to the number of iterations you can test, making it an invaluable way to learn what price makes the most sense.

Modernizing these methods of market research makes sense in today’s fast-moving retail world. Leveraging virtual simulations and mixed reality tools is one way retail insights professionals can gain accurate, actionable data—making sure their brand stands out in the crowd. Stay tuned for a deeper dive into each of these methodologies and how virtual is already making an impact in the space.

Contact us to Learn More about how you can get started with virtual market research.


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