Showrooming is one of the biggest problems in modern retail. Online stores offer a wide variety of products in stock with fast delivery and often at a better price than offline. However, customers still want to see and touch the product before purchasing, so they actively use offline retail stores to look at the product and then leave to buy it online.
This is the problem where AI can be helpful. Let's consider several cases of converting more audience to offline purchases or at least keeping them close.
First, you need to understand what percentage of the engaged and interested audience leaves a store without a purchase.
DISPL's audience analytics shows the peak times for traffic and leads on heatmaps. The first thing you can do is compare these numbers with sales. Peak times for traffic, but not for sales? It means that engaged people are leaving.
How do we know that the audience was engaged? We can track it by engagement with products (for example, picking up the sample device in the CE store) or by the time spent in front of the screen/brand zone.
It is a fact that sales are better when there are salespeople involved. So the first tip is to reschedule your sales assistants' working hours for them to work at peak times and increase conversion.
By the way, DISPL's Video Analytics will also tell you how effective your salespeople are by tracking the number of visitor interactions. An example of a graph based on the data is below.
You can see when your employees were in their assigned zone and how many leads they engaged.
When you ensure your staff is in their positions, help them sell. For example, the sales manager approaches a customer looking at a pretty expensive laptop. He is talking about the device's features and great value for money. Simultaneously, promotional content on the brand zone screen supports the narrative. What do you think? What is the probability that this customer will buy this laptop? About 10-15% higher than with regular sales.
A 10-15% higher probability of sale is still not 100% visitor conversion. But it's better to manage their life cycle than just let go. That's why the final option for this article is lead collection.
Lead collection is traditionally made with a form where a potential customer has to leave some data, like email, phone number, and name. Only a few people want to leave their personal info. That's why AI helps. When a person is interested in some item, let's say a phone, and they test it for several minutes, an offer can appear on that phone's screen. This offer can be something like: "Sale will be on soon! Leave us your contacts, not to miss the best deal on this model". A lead fills in the form, and that's it. You now have their data and can continue marketing communication online.
You will have their contacts even if the person leaves the offline store without a purchase! It means that you can convert even more traffic without doing anything.
Showrooming is a big deal for brick-and-mortar, and there's almost nothing you can do to eliminate it fully. Nevertheless, modern technologies make a great effort to work with the issue and help increase conversion and get a bit more in offline sales.
With practical examples and applications, the guide demonstrates how to use the insights obtained from these metrics to improve business strategies effectively.
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