BMW Group Japan
BMW Group Japan uses Cinarra to measure customer visits to BMW dealerships. Mr. Taro Saeki, the integrated communication manager of the Z4 sports car and retail marketing planner at BMW Group Japan, was in charge of the introduction. He is in charge of a wide range of marketing tasks, from web promotion to planning promotional materials to be distributed in stores.
What is the solution that can realize O2O marketing optimized for each dealer?
We asked him about the challenges he faced before introducing the solution and his impressions of using Cinarra.
We were looking for a tool to measure the effectiveness of web advertising for each dealer.
Could you tell us again about your company’s business and the nature of your work, Mr. Saeki?
Saeki: BMW Group Japan (hereinafter referred to as “BMW”) sells imported cars and provides after-sales service, support and maintenance. The main car brands we handle are BMW and Mini.
I have two roles in the company. One is “Integrated Communication Manager”. In this position, I am in charge of planning and managing integrated measures from advertising to in-store marketing for each car model.
The other is the “Retail Marketing Planner,” which provides support for various marketing activities rooted in dealerships. For example, we plan seasonal campaigns such as Christmas, commemorative gifts to be distributed to customers, and design stories for web marketing.
The “dealer marketing consultants” on the same team take the ideas of planners like me and incorporate them into each area’s dealerships. They visit the dealers and, in addition to propagating a unified nationwide campaign, they also understand the issues faced by each store and provide advice on how to solve them. In order to provide more accurate advice, it was necessary to visualize the effectiveness of the campaign for each store.
What were some of the issues you faced in terms of measuring the effectiveness?
Saeki: Previously, we were not able to visualize the effect of how many customers visited our stores after seeing our web ads. That’s why, in meetings with dealership marketing consultants, some dealers would say, “I don’t really understand the effect of Web advertising”. For example, when we conducted a test drive campaign, we knew the number of applications on the Web, but we could not measure the number of users who came directly to the dealership after seeing the advertisement.
In my previous department, I was in charge of market research, which is analysis based on numbers, so I felt uncomfortable doing web marketing without being able to visualize actual numbers.
When I thought of a way to measure visits to stores, I remembered Cinarra’s service. I knew of its existence before, but at the time, I couldn’t use it because my job was to analyze the market and I didn’t have the budget for advertising.
Now that I am in charge of marketing for Z4 and have a budget for advertising, I thought it would be a good time to try using Cinarra, so I made an appointment with them.
Using Dummy Ads to Elaborate on the Effectiveness of Advertising in Sending Customers
Thank you very much. You introduced “Real People,” an ad serving service, and “Real Sight,” a store visit measurement service. What appealed to you about these services?
Saeki: One is the ability to visualize the effectiveness of web advertising for each store. Each dealership faces different challenges, so for a dealership marketing consultant, the numbers for each store are more important than the national aggregate numbers. By utilizing these figures, we will be able to communicate with our dealers in a more appropriate manner.
Another attractive feature was the high accuracy of measuring store visits inside buildings. There are other geo-targeting services, but they use different positioning technologies: GPS is not good at measuring indoors and its accuracy is low, and for beacon, the customer has to download a special application. On the other hand, Cinarra uses Wi-Fi to exclude passersby based on the signal strength and time spent, which is highly accurate, and it does not require a dedicated app to acquire data efficiently, thus achieving a good balance between accuracy and volume.
Did you have any concerns when you introduced the system?
Saeki: Since I come from a research background, I was concerned about whether the measurement results could be effectively delivered. For example, let’s say that an advertisement for the Z4 happened to appear on the smartphone of a customer who was going to test drive the Z4 at a store. In that case, we don’t want to count it as an effect of the advertisement because we can’t say that the customer came to the store because of the advertisement.
When we discussed this with them, they provided us with a customized report for us. By dividing the target segment into two groups, a dummy group and a test group, and displaying dummy ads in the dummy group, we were able to estimate the number of store visits that were actually triggered by the web ads.
During the campaign period, you used the PDCA cycle to improve the delivery targets based on the analysis data, but what kind of results did you get?
Saeki: The biggest result was that we were able to quantitatively see the effect of web advertising on customer traffic, and we were able to see numerically how the unit cost per visit (advertising cost per visit per potential customer) was sometimes lower with web advertising than with souvenir distribution.
I think it is beneficial for automakers’ marketing to have this kind of “online to offline customer data” available. As a recent trend, more and more customers are coming to the store after gathering all the information on the web before purchasing a car. Therefore, it is becoming more and more important to know which contents and advertisements on the web have encouraged customers to visit the store in order to implement effective promotions.
Also, Cinarra can provide us with location-based persona and interest segment analysis reports, which will allow us to take a different approach. For example, this time we found that the performance of “people who go to the golf course once a month” and “people who visit luxury brands” was good. By analyzing these segments, we will be able to come up with the best targeting design for each car model.
We would like to analyze the effectiveness of the website in sending customers to the store, so that we can come up with further measures to increase the rate of visits to the store.
Please tell us about your future plans.
Saeki: First of all, we plan to report the results to the marketing consultants of our dealers so that they can make use of them in their communications with dealers. At the same time, we would like to share the results at the Marketing Department’s general meetings and disseminate the information internally.
We would also like to clarify the motivation for customers to visit our stores. For example, “I was interested in the campaign,” or “I want to test drive a model that a celebrity was driving”. However, the only way to find out the motivation was to ask customers to fill out a questionnaire.
Cinarra’s “VitalSight” allows you to track the number of customers sent to your website by website content. By analyzing the web content viewed before visiting a store, we can take measures such as placing popular car models in prominent locations in the store. I hope that Cinarra will continue to develop more and more useful tools for measuring store visits.
Finally, do you have a message for those who are considering Cinarra’s solutions?
Saeki: I think it is important to understand “how customers are being sent from online to offline” based on data. Even if you take a measure based on your sense of touch, it may actually be a big mistake.
In order to prevent such mismatches, we need to measure the effectiveness of how many people who have seen our web ads have visited our stores, and analyze customer trends quantitatively. By using Cinarra’s store visit measurement and unique segmentation, I believe we can create measures that are in line with the actual customer journey.