How do I use the InSight Analytics Platform?

1. Traffic & Awareness (Visitor InSight is a prerequisite*): Understand the volume and trend of Visitors coming to your locations, how long they stay, and the demographic breakdown of visitors. You can also understand the effectiveness of screens in your locations if you have our CX product.

2. Content Engagement (Raydiant CX is a prerequisite*): Get insights into not only the playback stats (playback time, distribution) but also the effectiveness/performance of the content based on how many people viewed the content and for how long if you have our Visitor InSight product.

3. Product Engagement (Lift and Learn is a prerequisite*): Understand shopper engagement at shelves, and interactive screens/kiosks, based on the volume of product pickups, and screen clicks on content related to products.

Glossary of Metrics

Traffic & Awareness Metrics

• Traffic (also known as “Opportunity To See” or OTS): Number of people in the field of view of the camera/s in your locations. This is your total potential audience.

• Unique Impressions: Number of people that at least had a glimpse at your screen(s). We measure where they are looking and count anyone who is gazing within 45º of the screen.

• Verified Viewers: Number of people that looked at your screens directly.

• Engaged Viewers: Number of people that looked directly at your screens for at least 2 seconds.

• Engaged Shoppers: We define a “Shopper” (vs. a “Viewer”) as someone who has picked up one of your physical products on your shelves or clicked on your information on interactive screens. We count the number of shoppers by these interactions, with each shopper session defined as a series of interactions with less than 60 seconds in between. After 60 seconds with no activity, we start a new shopping session. *Note: This metric is only available for our Lift and Learn Customers.

• Screen Placement Quality: This is the conversion rate from Traffic to Unique Impressions, and indicates how well your screens are placed in getting attention from Traffic coming into your locations. For example, if your screen is hidden in a corner and hard to see, a lot of foot traffic may not see it, and this conversion rate will be low, indicating a problem you can address. Your screens are rated from highest to lowest Screen Placement Quality on your Traffic And Awareness section.

• Verified View Rate: The conversion rate from Unique Impressions to Verified Views, indicating the effectiveness of your content in getting the attention of people. Content that has animation, motion, and video tends to get attention better than static content, and certain color designs can improve this conversion rate.

• Avg. Dwell Time: The time in seconds that people spend in your locations in front of your cameras.

• Avg. Viewing Time: The average time in seconds that people spend looking at your Screens. This is only available if you are using both Visitor InSight and CX.

Content Engagement Metrics

• Total Playback Time: The total amount of time in seconds that a piece of content has been played across all of its playbacks. You can use this to see what percent of time each content is being allocated on your screen network.

• Playback Distribution: The share of playback time of a piece of content out of all your content that’s being played.

• # of Plays: The number of times a content has been played. You can use this to verify playback to advertisers or see how often content is being triggered by Rules and Tags.

• Traffic (OTS): Total number of people that were around the screens when your content was being played. People are recounted for each piece of content played so this number may be more than Traffic (OTS) the Traffic & Awareness where traffic is counter per screen. You can use this to provide overall reach to advertisers.

• Content Impressions: The number of times customers have got at least a glimpse of your content. You can use this to provide verified impressions to advertisers.

• Content Views: The number of times customers have viewed your content.

• Content View rate: The conversion rate from Content Impressions to Content Views.

• Avg. Viewing Time: The average time (in seconds) people spend viewing your content measured in seconds.

• Last Time Played: The timestamp (in the 24-hour notation) that a piece of content was last played on your network.

• Tags/Locations: The number of locations where a piece of content has been played.

• Top Button: The button (i.e. any clickable element on the screen) with the most tracked clicks on an individual page.

• % Clicks on page: The percentage of the clicks a link/button gets on a page. It is calculated by the # of clicks of that button divided by the total clicks on all buttons on that specific page.

• Page Type: Pages categorized and grouped by their goal/functionality. Use a page type to compare pages that are like each other in performance. For example, for a shopping experience, each product detail page (or what’s called a PDP in eCommerce) may be one type, a “Ratings and Review” page for each product might be a separate Page Type, “Product Video page, etc. In this way, you can compare the performance of each piece of content against like pages, or look at the overall performance of a page type, like how often shoppers engage with Ratings And Review pages vs. Video pages so you can prioritize the types of content shoppers want most.

Product Engagement

• Total Interactions: The sum of all product pickups at a shelf plus all the button/link clicks on an interactive screen. This is a measure of success in how engaging your merchandising and interactive digital content are and how much you are influencing shoppers at key purchasing moments.

• Screen Clicks: The number of times a shopper has clicked on a button/link on a screen. Each button on a screen must specifically be encoded to be tracked using the Raydiant SDK.

• Product Pickups: Number of pickups of each product at a shelf using our Retail Experience (RX) sensors. Shopper marketers use this to understand if the planogram design is driving shoppers to pick up their desired products and whether the planograms are performing as expected. For example, one client found that the edges of an end cap at a grocery outperformed the adage that the best place to keep your products is center and eye level.

• Engaged Shoppers: We define a “Shopper” (vs. a “Viewer”) as someone who has picked up one of your physical products on your shelves or clicked on your information on interactive screens. We count the number of shoppers by these interactions, with each session defined as a series of interactions with less than 60 seconds in between. After 60 seconds with no activity, we start a new shopping session.

• Pickup-to-screen conversion rate: Number of screen clicks per pickup by product. This is a measure of how effectively the digital content engages a shopper after they pick up a product. You can use this to identify how different experiences engage or if a specific product is over- or under-performs. For example, a beauty client found that one of its product lines had the highest Pickup-to-Screen Conversion Rate and it was the only product using Instagram influencers instead of celebrity spokespeople in the videos. They updated all product videos to have influencers and saw a 20% increase in content engagement (aka “Button Clicks”) and a 10% increase in sales!

Insights and Actions

Filters

1. Locations: This filter lets you select the location for the scope of the data. For now, you can either look at data of all your locations, or you can choose to look at one location at a time. Shortly, we’ll add support to be able to select multiple locations and look at their data together. The default is All Locations.

2. Date Range: This filter helps you select the scope of time for which you want to measure the data. You have the option to choose the last 7 / 30 / 90 days, All Time, or a Custom Date Range. The default is the Last 30 Days.

Traffic & Awareness

• How are the overall traffic and other metrics affected by a new campaign?

• What are the numbers of Total Traffic, Verified Viewers over a specific period?

• What are the daily and weekly averages of Traffic, Unique Impressions, and Dwell Time?

• Are these numbers up or down compared to a similar period before?

• Where is the biggest drop-off? Do I lose more at converting Unique Impressions to Verified Viewers? Or somewhere else?

• How does the funnel look at my biggest locations (use filters) vs others?

• Do new content campaigns change traffic conversion?

• Look at how the funnel looks for different locations.

• If for example, you see that some of the locations don’t have the drop-off, and only some do:
• Then you can look at the difference between the Screen placement in these locations.
• It could be that in the locations with the drop-off, the Screens are not placed where customers walking in can look at them easily.

• How does the trend of Traffic compare to the trend of Verified Viewers?

• How does Average Dwell Time change compared to the peaks and Dips of Traffic and Unique Impressions?

• Are there any sudden or unexpected spikes or drops so you can find causes?

• How did the Traffic change in the locations with increased Dwell Time? Maybe they had more customers coming in, and hence longer Dwell Times.

• Check if there are any differences in the store design. Maybe the stores with decreased Dwell Time had good entry and exits for efficient traffic flow?

• What are my top-performing locations/stores by Traffic vs engagement (in terms of how long they stay i.e. Dwell Time)?

• Which stores are seeing the biggest change in traffic or engagement based on my marketing programs and targeting?

• How are the underperforming stores faring in incoming Traffic? Are you getting increased Traffic without being properly equipped to handle it?

• If serving Visitors more effectively (i.e. decreasing dwell time) is the goal, are there differences in the operational procedures of the stores performing poorly?

• Check for differences in screen placement between well-performing stores and underperforming stores to understand the difference in Unique Impressions.

• What times are bringing the most traffic on different days in different locations?

• How does Traffic correlate with Dwell Time? If you see a surge in traffic, does Dwell Time increase because of longer lines or are you staffed optimally to handle the loads?

• Are there any surprises? For example, an ice cream client sees surges of (younger) clients when schools get out and some of our restaurant clients see surges in traffic on Sunday afternoons around youth sports games.

• What are the dominant demographics?

• Are the locations personalized enough for the demographics to boost engagement and customer satisfaction?

• Which age groups dominate on weekdays vs weekends?

• Are you running special promotions that are relevant to different age groups on different days?
1. You can soon better understand which campaigns work best on different age groups in the Content Details Page.

• How is the male vs female split on weekdays vs weekends?

• How does the distribution change compared to the overall traffic change?

• Are the promotions in the location tailored to the correct Gender on different days?
• You can soon better understand which campaigns work best on different genders in the Content Details Page (*coming soon).

Product Engagement

• How are the overall numbers looking after a new campaign is up and running?

• What was the number of Engaged Shoppers over a specific period, and what the daily and weekly averages were.

• The total amount of product engagement (Product Pickups + Screen Clicks) across your digital network.

• How well your interactive content is engaging shoppers by converting them from picking up a product to clicking on the screen.

• Are these key measures of success going up or down?

• How does the trend of clicks compare to the trend of pickups?

• How does the trend of Engaged Shoppers compare to clicks and pickups?

• Any sudden or unexpected spikes or drops in activity?

• What is the trend of engagement (pickups, clicks, and sessions) on weekdays vs weekends?

• Check the difference in awareness of the customers in locations with an uptick vs locations without an uptick.

• Check if there are any differences in design. If you have 50 or more locations, many customers run different content to do A-B testing to find out what content works better to drive engagement and sales lift.

• Check if locations without an uptick in clicks have working touch screens and proper content triggering after pickups.

• How is my planogram performing compared to expectations? Are the most important products effectively promoted? For example, often clients find that engagement on the edges of fixtures is higher than expected.

• What is my best-converting content for each product? One client found that products that used Instagram influencers converted better than those with famous spokespeople.

• Make the content on the product pickup page more attention-grabbing or relevant.

• Increasing the prominence of the calls-to-action by examining the design and enhancing it to be larger, more colorful, or animated.

• Optimizing screen placement in the fixture (eg: moving it closer to visitors) will improve the conversion rate.

• Reevaluating if the content you are offering is the right next step in the education process. Ask shoppers what questions they have and what they need to know at the moment of consideration or evaluate whether the content is too busy and confusing.

• Review which products are driving the highest pickup-to-screen and see if there are any patterns or learnings.

• What are my top-performing locations/stores by shopper count or engagement?

• Are any of my stores no longer recording engagement? Perhaps they are offline, have been unplugged, are broken, or you may be out of product.

• Which stores are seeing the biggest change in traffic or engagement based on your marketing programs and targeting?

• How are the underperforming stores faring in pickups and clicks? Is either particularly low? If only pickups are low, for example, you can investigate further into whether it’s because the product is out of stock, product placement in the store has low store traffic, or if equipment is malfunctioning.

• Check for differences in product placement between well-performing stores and underperforming stores.

• Check if customers are aware of marketing campaigns that are running. You can use Raydiant Visitor InSight to do this automatically at scale with data on several people watching, the demographic breakdown, and the length of viewing sessions.

FAQs