Home Advertiser DHL’s Strategy To Make Its Marketing Data Deliver

DHL’s Strategy To Make Its Marketing Data Deliver

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DHL box and a crumbling cookie
For DHL Express, preparing for the end of third-party cookies and prioritizing its own first-party data come as a package deal.

For DHL Express, preparing for the end of third-party cookies and prioritizing its own first-party data come as a package deal.

“‘Cookieless’ is just a buzzword,” said Sanup Pillai, DHL’s global head of digital marketing and mar tech. “I wouldn’t say we’re getting ready for the ‘cookieless future’ as much as that we’re taking this opportunity to future-proof our technology stack.”

Although DHL has access to a lot of first-party data through direct relationships with both B2B and B2C customers, that data wasn’t doing much for DHL because it had been sitting in an outdated, homegrown CRM database that didn’t have integrations with other mar tech systems.

It was the definition of a silo.

Righting the ship

The first thing DHL did was find a new CRM system to organize and manage its data and start the process of shutting down its legacy system. Pillai and his team are going through the onboarding phase now.

Next, DHL plans to partner with a customer data platform to help with more advanced use cases, including look-alike modeling. DHL is kicking the tires on a few different CDP potentials.

“CRM is a big data source for a CDP, which is why we had to make it our first priority,” Pillai said. “Without CRM, a CDP is useless.”

DHL has also been rethinking its customer journey. Pillai acknowledges that the user flow on the DHL site has historically been less than seamless.

For example, there are multiple places where someone can go to create an account, multiple pages where someone can initiate shipping and multiple pages with information about taxes and custom duties in different countries.

Simplifying the online experience should help DHL collect more first-party data in the absence of third-party cookies.

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“Using third-party cookies was always the easiest way to determine how someone behaves on a website,” Pillai said. “Without them, we now have to focus more on deterministic data, which just isn’t as easily available.”

AI insights

Although DHL is making progress with its revamp focused on first-party data, change takes time at very large companies.

Pillai estimates it’ll be well over two years before DHL is able to fully deploy a new CDP and roll it out across markets.

In the meantime, DHL has been looking for a few quicker wins, including ways to save money on digital marketing.

For example, DHL has poured a lot of ad budget into social, search and display, but “we haven’t always dug deeper to know how much these investments are really helping us,” Pillai said.

DHL recently started working with a small outfit called Pixis that allows marketers to monitor their campaigns and automatically make AI-based budgeting and creative optimization recommendations based on context.

Pillai said he “stumbled” on Pixis in a startup incubator and that the company appealed to him because it has a no-code setup, meaning little to no programming necessary.

“I see software-as-a-service as the way forward, because it’s easy to integrate and easy to get started,” Pillai said.

Pixis has plugin integrations with a handful of the largest ad platforms, including Facebook Ad Manager and Google Ads. The plugin tracks and compares performance across platforms and runs experiments against audience cohorts within a marketer’s target audience.

Based on the results, Pixis recommends specific actions to reduce the cost of acquisition and boost ROI, such as updating bids, refreshing creative or tweaking the targeting parameters.

During a pilot test with Pixis in India, DHL was able to narrow its targeting to focus on five specific priority cities. Within about a week after uncovering that insight, DHL saw a roughly 20% increase in viable leads and a reduction in its overall cost per lead.

“From a marketing perspective, AI helps us be more efficient when it comes to handling data by taking away the manual intervention,” Pillai said. “That’s time we can use for better things, like uncovering insights and using them to deliver results.”

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