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On our weekly date night, my wife and I usually order pizza for our kids from a food delivery app before heading to our favorite restaurant. One Friday, the pizza looked like it had been dropped by the delivery driver. There was no way I’d serve it to my children. I reached out to the delivery app’s customer service to replace the pizza but was told it would take several hours. The best they could offer me was a credit on my account.

Compare that to our experience with Waze once we got in the car. Not only did Waze give me accurate directions to our date-night destination, but it also provided the fastest route, avoiding an accident on the freeway and a pothole along the way. It not only delivered the basic service I needed — navigation — it anticipated what I wanted, providing a personalized experience that was the very opposite of my tone-deaf pizza delivery.

In 2019, customer experience is king. Services like Amazon and Apple have raised consumers’ expectations for the level of service and personalization they’ll receive. Many companies, like Waze, are not only meeting but exceeding expectations by proactively anticipating what customers want. This differentiates these winning brands from their competitors.

But too many others — like my pizza delivery company — are still failing at this. Is it because they don’t understand the challenge? Or because they don’t have the tools they need to meet it?

Marketers struggle to use post-sales data effectively

Today, businesses increasingly recognize the importance of prioritizing customer experience, and for good reason: Consumers say they’re willing to spend 17 percent more at businesses that provide excellent customer service, according to research by American Express.

But guessing what customers want is no longer enough. Today, companies are attempting to harness the power of data to predict their customers’ desires with new precision. In fact, research shows that companies plan to nearly triple spending on analytics within the next three years.

While I applaud this, the reality is that most organizations lack the data expertise and technology to make it happen. Although plenty of marketers are eager to use data to improve customer experience, many describe their current technology as “fragmented” and “inconsistent.” Throwing more money at the problem won’t change anything unless marketers become more adept at understanding the data they collect.

That was certainly the case for the food delivery app. Over the weeks that followed my delivery disaster, the gaps in their use of the data they have on me became glaringly clear. I received relentless emails asking me to rate and review my experience — even though I had already provided negative feedback to customer service. I had clearly been added to a list of past customers but not  to a list of people with customer service complaints.

And every 10 days, like clockwork, I received an automated message nagging me to use the $24.95 credit I’d been given for the ruined pizza. The company’s marketing outreach didn’t differentiate between happy customers and ones like me, who might need more convincing to come back. Perhaps the company hadn’t collected the data from my support interactions or used it to inform their marketing outreach — but as their customer, I expect them to understand me regardless of the channel or type of interaction. As a result, I got angrier and angrier. I spent eight months ignoring that credit, opting to try other delivery services instead.

Post-sales data can build deep customer relationships

When used correctly, post-sales data can help marketers identify new conversion opportunities, spot inefficiencies that can be resolved, and brainstorm ideas for campaigns or promotions. Instead of just trying to resolve problems as they occur, companies should use post-sales data to provide proactive product recommendations or re-engage lapsed customers with offers they actually want to engage with.

Imagine if the food delivery app gave drivers the ability to quickly and easily record customer feedback at points of interaction. Instead of shrugging off my questions, the driver could have noted my bad experience on the spot, prompting the company to automatically send an apology and a coupon for free pizza next time. It’s tough to market to someone who’s upset, but the quick response would have impressed me enough to give them a second chance.

When companies use post-sales data effectively, they build incredibly deep, defensible customer relationships. By behaving like a friend who’s watching out for the customer rather than a brand trying to sell them something, companies earn trust.

And that trust can earn huge dividends. For example, Waze’s approximately 50 million users don’t just use the app to find their way. Much of the company’s annotated map data actually comes from users themselves, who volunteer their time as map editors. Some are so engaged that they voluntarily spend 30 hours a week or more adding information such as updates about construction or road closures to Waze’s massive repository, all without pay.

The path to data-driven customer experience isn’t one that’s only open to the Apples and Amazons of the world. Focusing on post-sales data is a powerful way for even the smallest companies to even the playing field and compete with the Amazons of the world. No matter how often your target customers hop online and sort by lowest price, if you use data to deliver unforgettable customer experience, they’ll keep coming back.

Post-sales data levels the playing field

As more marketers turn to data to improve customer experience, they’ll need to think more like Waze and less like the pizza company. Marketers need to ask themselves how data can help them deliver an improved customer experience that aligns with their organization’s overall mission. Data should power more personalized campaigns and outreach, connecting customers to offers they’re excited to engage with instead of generic messaging that’s easy to ignore.

Data-driven, service-oriented marketing isn’t a new idea. But most companies can improve the way they leverage post-sales data — and improve their customer experience along the way.

Shawn Myers is a Director of Product Marketing at Oracle.

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