More than two-thirds of corporate marketers say they plan to increase their data and analytics budget this year, according to a recent study. 89% said they already use data to make marketing decisions. 98% use data to make their case for yearly budgets. And 70% use data to make an impact on high-level business goals.
If you’re in marketing these days, chances are you’re either already using data to improve your marketing outcomes or you’re scrambling to catch up with those who are. And if big data-driven results are the goal, you’re probably looking for examples of companies getting it right.
The good news? The list is a growing one, and lots of companies are sharing what works for them.
8 examples of companies doing big data right
Let’s start with one of the big guys. Not only does Amazon have some of the best AI, machine learning, and predictive analytics out there, they also have a whole team dedicated to their personalization and recommendation engines. These engines, driven by customer data, use past purchases, ratings, reviews, etc. to identify what a customer is likely to buy and when – serving up the right recommendations at the right times.
This strategy, as you’ll have guessed, is paying off big for the retail giant. An estimated 35% of all of Amazon’s sales come from its recommendation engine—driven by customer data.
For Nestle Purina’s Petfinder.com, harnessing the power of big data led to a 300% jump in conversion rate and 90% drop in cost per acquisition.
The journey started when the brand implemented Lytics CDP to collect and connect their customer data. They then used our behavioral scoring feature to identify customers who were highly engaged and had recently searched for baby or young dogs.
This led them to highly qualified buyers who they could target with personalized messages about young dog adoption and products for young dogs. And this was the campaign that catapulted them 300% past their usual conversion rate.
For The Economist, it all started with a commitment to customer centricity—which meant a commitment to collecting customer data, gathering insights from it, and using those insights to better connect with the real people they serve.
They used Lytics predictive scores to identify the right customers for each marketing offer and serve up those offers at the right time. And the results of this data-driven approach were again staggering: a 300% increase in subscriptions and an 80% drop in customer acquisition costs.
Fitness industry darling Peloton is another brand to watch when it comes to big data. The company uses data to personalize emails for their members, with workout schedules and activity recaps just for them.
This strategy has the fitness brand knocking industry email open rates out of the water—with a 48% average open rate on their intro email and high rates on subsequent emails as well.
Another industry leader you’ll recognize, we all know that Netflix has the big data thing down.
Even as far back as 2016, the streaming service’s data science-driven recommendation engine saved the company an estimated $1 billion per year and influenced about 80% of everything that streamed on the service. And now that they’ve turned their predictive analytics on content creation, they’re raking in successes like House of Cards and Bird Box.
Kroger used big data in a rather unusual way—to personalize direct mail coupons to their existing customers. To do this, they used data from their robust, well-ranked customer loyalty program, sending the right coupons to the right customers at the right times.
The average coupon return rate in the industry is 3.7%, but Kroger’s data-driven approach? It earned them a whopping 70% coupon return rate.
The Motley Fool
When The Motley Fool set out to become more data-driven, they focused on using data to identify high-lifetime-value prospects. They then used what they knew about those high-value customers to create lookalike audiences that targeted similar prospects who hadn’t yet interacted with the brand.
Using data to hone their efforts like this saved The Motley Fool 20% on customer acquisition for their highest-lifetime-value targets.
We talk a lot about data, but the truth is that all these success stories are only possible because of insights from that data. And Airbnb is another company that takes those insights very seriously, using data science to glean insights to improve both product and marketing.
In fact, when a data scientist at the leading booking platform shared the insight that consumers in China, Japan, Korea, and Singapore had a different customer journey than customers elsewhere in the world—and that journey was getting derailed by Airbnb’s normal setup—the brand rushed in to make changes for those geographic regions.
The result was a 10% increase in conversions from those countries.
Big data and your marketing
As you can see, big data is making a big difference for companies doing it right. If you’ve thinking about how to harness your own data for these kinds of results, we’d love to talk about how Lytics CDP can help.