CL (Chantelle Lingerie): Revealing the true ROI of online marketing
About CL (Chantelle Lingerie)
Founded in 1876, CL is a leading international producer and retailer of women’s lingerie with 10,000 sales outlets worldwide, 400 stores, and annual revenues of €400 million.
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OWOX BI provides analytics services for multi-channel businesses and helps implement Google Analytics 360 Suite and Google Cloud Platform projects.
CL revealed ROI from online advertising to be five times higher than previously estimated by using Google BigQuery and the OWOX BI Pipeline to match online customer behaviour to in-store purchases.
Google Cloud Results
- Combines online and offline information on customers to optimise media spends
- Reveals digital influence on 35% to 40% of all retail group revenue
ROI from online marketing calculated as five times higher than previous estimates
Founded in 1876, CL has expanded rapidly in recent years through organic growth and a series of acquisitions. Today, the company operates eight brands, each with their own markets, ecommerce websites, or shop networks, including Chantelle, Chantal Thomass, Passionata, Darjeeling, Femilet, Livera, and Orcanta. Together, the brands account for €400 million of turnover a year, making CL one of the leading players in the European market.
Half of the group’s revenue is made through wholesale channels, and half through direct retail. “Of our direct retail revenue, up to 95% of our turnover is made in our physical stores and only about 5% is from digital sales,” says Christophe Lemaire, VP of e-marketing, Acquisition & CRM at CL. “That means that when we make data-driven decisions to manage our online experience, we need to have access to offline data.”
“We used Google BigQuery to create a unique customer database for our retail networks inside CL. It is simple to set up and, unlike a black box solution, it enables access to all of the data we stream to it. It’s important to see data when you work with it—a misunderstanding can make the whole system inaccurate.”
—Christophe Lemaire, VP of e-marketing, Acquisition & CRM at CLAs the person responsible for CRM activities and online marketing, Christophe recognised that CL’s online marketing was seriously undervalued. “To do a good job in terms of online marketing, we have to calculate the ROI of our actions based on the turnover we generate online and offline,” he says. “But because we were only calculating that ROI based on online revenue, we were underspending on digital media.” Combining online and offline sales information could do more than paint a clear picture of true customer behaviour, too. “To personalize online marketing for customers, we need to use information from offline transactions to establish preferences and make recommendations,” says Christophe. “Displaying the right product to a customer means making reference to our CRM database, too. For example, we can calculate sizing for customers through their history of purchases, so we can be sure that a product we recommend to someone is in stock in their size on the website.”
That meant building a unified customer database to run across all of CL’s retail networks, combining online behaviour with offline sales to build true profiles of customer behaviour. To do that, CL built a solution on Google BigQuery.
“We used Google BigQuery to create a unique customer database for our retail networks inside CL,” says Christophe. “It is simple to set up and unlike a black box solution, it enables access to all of the data we stream to it. It’s important to see data when you work with it—a misunderstanding can make the whole system inaccurate.”
Combining online and offline data with Google BigQuery and OWOX BI
Calculating the impact of online advertising on ROI is a challenge for retailers that make most of their sales in brick-and-mortar stores. Previously, CL sent online user behaviour data to Google Analytics and offline sales and orders information to the company’s CRM system. Because the two flows of data were not combined, the company had no clear picture of the relationship between a customer’s online and offline activity.
“The first technology we began working with to create a database was not very mature,” says Christophe. “Like many products of its type, it was a black box. That’s when we discovered OWOX BI and Google BigQuery. We set to work and it was really straightforward. One quick configuration and all of our online behavioural data was in Google BigQuery. We knew then that it would be easy to move the CRM data, too.”
“The hidden cost behind many solutions is that you need to have very specific skills in-house. That wasn’t the case with Google BigQuery. With existing IT team members already working on BI at CL, we have been able to manipulate the platform ourselves.”
—Christophe Lemaire, VP of e-marketing, Acquisition & CRM at CLUsing the OWOX BI Pipeline, user interactions with CL websites are sent in near real time to Google BigQuery, which delivers the processing power necessary for producing complex customer reports at speed. By creating user ID values based on customers’ loyalty card numbers and applying them retroactively, OWOX BI identifies 30% to 50% of past sessions as well as ongoing activities. At the same time, CL marketers import data about completed orders to Google Cloud Storage every day, which is then sent on to Google BigQuery, where data on online sessions is merged with order completion rates in a single table under the unique ID value. To visualize the results, CL uses Sheets and dashboards on Looker Studio. This is what the data flow looks like:
“The hidden cost behind many solutions is that you need to have very specific skills in-house,” says Christophe. “That wasn’t the case with Google BigQuery. With existing IT team members already working on BI at CL, we have been able to manipulate the platform ourselves.”
“We want to stop retargeting users on display based on offline data. As far as we know, no retailers do that. With our integrated data we can now see if a user has made a purchase and make an asynchronous connection with the ad retargeting platform to ask them to stop, so we waste less money, avoid annoying our customers, and focus our media budget on more effective channels.”
—Christophe Lemaire, VP of e-marketing, Acquisition & CRM at CLOptimizing media spends with clearer customer journeys
Thanks to the new solution, CL can see the true ROI of online marketing more clearly. “We extrapolate that for every online sale attributed to online marketing, we make five offline sales from the same source,” says Christophe. “That means we can multiply our ROI by five, at least by extrapolation and reflect that in our digital marketing budget.” CL now estimate that between 25% and 30% of offline retail sales are influenced by digital marketing, and up to 40% of overall retail turnover is digitally influenced. In addition, customers influenced by digital marketing appear to spend more in their purchases, as Anastasia Chausova at OWOX BI explains: “We figured out that customers who research online before buying offline demonstrate larger average revenue both per user and per order. They spend more money, and that’s a valuable insight.”
Now CL is looking to use its newly integrated data to improve customer experiences directly while saving money, by stopping ad retargeting to users who have already made a purchase offline. “We want to stop retargeting users on display based on offline data,” says Christophe. “As far as we know, no retailers do that. With our integrated data we can now see if a user has made a purchase and make an asynchronous connection with the ad retargeting platform to ask them to stop, so we waste less money, avoid annoying our customers, and focus our media budget on more effective channels.”
Tell us your challenge. We're here to help.
Contact usAbout CL (Chantelle Lingerie)
Founded in 1876, CL is a leading international producer and retailer of women’s lingerie with 10,000 sales outlets worldwide, 400 stores, and annual revenues of €400 million.
About OWOX BI
OWOX BI provides analytics services for multi-channel businesses and helps implement Google Analytics 360 Suite and Google Cloud Platform projects.