If you are in charge of attracting customers to a retail business such as a beauty salon, bridal salon, or accommodation facility, you may have had concerns like these.
For brick-and-mortar businesses, understanding whether online reservations lead to actual store visits and improving store visit rates is an important point in improving the cost-effectiveness of advertising.
So, how can you find out whether users who made online reservations via ads actually visited your store and increase the visit rate?
This time, we will introduce a case study of support for a beauty salon , a brick-and-mortar business , to understand and increase the rate of foot traffic via advertising.
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Table of Contents
Understanding store visit rates via advertising is not as difficult as you might think
The impact of "budget allocation" cannot be underestimated
summary
Understanding store visit rates via advertising is not as difficult as you might think
Naturally, to improve store visit rates, you first need to understand that users who made online reservations "visited the store." Generally, it is not that difficult to understand the store visit rate from "all" online reservations, but the hurdle increases when the filter "via advertising" is applied. However, understanding the store visit rate via advertising is actually not that difficult . There are several ways to do this, but we will introduce a relatively easy one.
This time, we will introduce some examples phone number database uk of how " ADEBiS" *1 was used.
Our company often implements ADEBiS mainly for attribution analysis (calculating TCV and TCPA) and to understand duplicate conversions. In this case, the main purpose was to understand duplicate conversions, but by using the " conversion attribute information *2" provided by ADEBiS, we were able to understand the store visit rate.
Conversion attribute information is a function that allows you to obtain non-personally identifiable attribute information of users who have made a conversion, such as their customer ID, device, membership number, and sales amount.
In this case, by matching the " reservation ID ," by ADEBiS , with the " user ID " in the client's database, it was possible to determine whether users who converted by making a web reservation actually visited the store.
The diagram below shows what it would look like when the "reservation ID" from the conversion attribute information obtained by ADEBiS is associated with the "user ID" from the client's database.
In this case, before determining the store visit rate, it was assumed that the store visit rate for users who made online reservations would be around 60% . However, after tallying up the data, it was found that the store visit rate via advertising was 35%, which was lower than expected .