Historically, Clorox’s products have been sold primarily in big box stores. And though that is still the case, the company has seen double-digit growth in its e-commerce business in each of the past two years—a trend that Web Analytics Group Manager Kesha Patel is responsible for maintaining.
That’s why she – and her team at HiddenValleyRanch.com – decided to bet big.
Kesha, part of a cross-functional team of data scientists, developers, analysts and product experts, had the goal of increasing the engagement of their best customers on the website for one of their brands. Success came quickly.
Hiddenvalleyranch.com saw a 30% increase in engagement, and now they have a powerful tool that can be deployed across their portfolio.
How they did it
Clorox’s wide variety of brands and forward-looking leadership allowed for more experimentation than would be possible at other companies.
However, it was quickly apparent that the most obvious idea of what to do with these websites was not going to be a feasible solution.
“We don’t really get sales from our site. It’s not something we do, and if we approach the website as a sales portal, we’re setting ourselves up for failure,” Kesha said.
Instead, the Hidden Valley Ranch team used the website as a destination to engage users with content related to the products to develop brand loyalty. To that end, they decided to run an experiment on the Hidden Valley Ranch site, testing these questions:
Will a personalization engine increase retention and engagement on the website? And what would that look like?
Kesha knew there were two metrics that she really cared about.
In order to measure the effectiveness of this experiment, Clorox implemented analytics into Hidden Valley Ranch’s personalization engine.
Help from product analytics
The personalization engine they built was not a massive overhaul of the website, but a few simple adjustments.
Instead of the same hard-coded recipe recommendations on specific pages going to everyone, viewers would now see recommendations based on what pages they had previously visited. The team needed someone who could build an algorithm to power the engine.
Fortunately, Naveen Kolagatla, a Data Scientist, was more than capable. He knew where to start:
“We needed to track and collect both registered and anonymous user data on our site.”
The process required Naveen to not just take in data, but to interpret it with the kind of complex analytics that serve as the backbone of any personalization engine. “We built statistical models to dig deep, and saw the evidence suggesting that personalized recommendations would delight our customers.”
Naveen couldn’t do it alone. “We realized personalization was a team sport,” Naveen told us. “We had tagging/analytics, developers, creative development, copywriters and brand folks working together to make this happen.”
Kesha agreed: “If we were going to do this project, it was imperative that we track the results to make sure we were spending time and money wisely.”
Personalization pays off
“We ran an A/B test at the beginning of this year,” Naveen said. “Our results were positive.”
“Consumers who received the personalized experience viewed 3x more than consumers who received the static experience.”
A more surprising aspect of this test was consumers were organically exploring a wider variety of recipes after being exposed to personalized test.”
After launching with a personalization engine that only targeted return users, the lift was undeniable.
Hidden Valley Ranch’s personalization engine was able to hold users’ attention and keep them actively engaged on the site for longer. Time and time again, they found the suggestions from the personalization engine to be delightful.
“The lessons of the Hidden Valley Ranch personalization engine experiment transcend the brand,” Kesha said. “If we can serve content that consumers are interested in, they will engage with it. And there’s a clear line from increased engagement to increased sales.”
Kesha was clear about one thing: if you want to have a personalization engine, you need the data upon which you base your underlying assumptions to be good.
“I think so many companies struggle with data integrity–trusting that what they are looking at is accurate. Because if that foundational data is not accurate, then what is a team supposed to do? Make sure you do things right the first time, otherwise you have to reimplement and instrument everything differently.”
Naveen agreed: “Follow the data! Start with small tests and scale big after you see the value.”
Kesha was excited about the potential for the personalization engine. “There is no shortage of brands that Clorox can use it on. Burt’s Bees, Kingsford, Soy Vay, Formula 409, and Fresh Step all represent exciting opportunities. We’re looking at it now, but it’s something you’re going to see rolled out across our brands in the future.”