Even as late as 2022, only 21% of consumers reported that they woke up feeling refreshed and rested. Sleep is one of the biggest problems plaguing the modern world, and Wakefit set out to solve this with scientifically designed mattresses and sleep solutions. Launched in 2016, the brand aims to democratize sleep and home solutions for the modern Indian consumer. Today, the D2C brand caters to over a million customers each year across the country and has grown 50% y-o-y.
“For a D2C platform, understanding the customer is key to cracking the market. For this, we need deep insights into the customer’s actions, buying patterns, and behavior.”
– Abhishek Mishra, Senior Growth Manager, Wakefit
In this blog, we take a deep dive into the product and growth function at Wakefit to understand 3 core strategies that have helped the brand crack discoverability, engagement, and conversion.
We all use mattresses. Life is almost impossible to live without one. But mattress protectors? That’s a whole other story.
It’s difficult enough to build a brand selling something as essential as a mattress, but how do you push consumers to buy novelty items like mattress protectors? This is difficult in a cost-conscious country like India, where the majority of the population has never heard of mattress protectors.
While the marketing team was able to build a good brand position around this product and introduce it as a new category, it still didn’t get traffic or engagement. Why? It was time to find out.
The team applied Behavior Analytics to understand and map every movement of every customer. They soon noticed that the product description page of the mattress protector was getting little to no clicks compared to the others. The team performed a root cause analysis and figured out that visibility of the product was low on the website and app.
Discoverability was the core issue.
Once the core problem was identified, the team could get started on a solution. They introduced a combo widget that showed the mattress protector as a combo to anyone who landed on the mattress page.
Within 30 days, sales of mattress protectors had increased by over 70%! This is a great example of product-led growth, where you make changes to the product based on customer behavior, and steer the brand toward growth.
A report from McKinsey found that cross-selling can increase sales by 20% and profits by 30%. This holds true for Ecommerce and D2C brands, where customers often get tempted to add that extra item to their cart if it looks good enough of a fit for them.
It’s crucial to maximize revenue from this channel because this is where customers have high intent and purchasing power. All brands need to do is recommend the right products to them. This might seem easy, but seasoned marketers know that it isn’t always just a click of a button.
The folks at Wakefit realized the same thing. As a general practice, they had a cross-selling engine that recommended products to customers during checkout. These recommendations were not backed by data, but by intuition. Was that good enough? Time to find out.
The team performed a thorough Funnel Analysis to understand how customers were moving from one point in the purchase journey to another. They discovered that engagements, clicks, and add to cart/add to wishlist activities were low in the recommendation widget.
Based on the information they obtained from Funnel Analysis, the team was able to build recommendations for products where conversions were higher than the others.
This reiterated recommendation engine helped Wakefit increase revenue by 2X within just one quarter.
Curious about how your recommendation engine can be better? Book a free consultation!
Picture this. You see a great product on a fun new website, add it to your cart, and get ready to make the purchase. The website tells you that you need to log in/sign-up for a better experience, so you go ahead. Unfortunately, the login/sign-up process is tedious, and you realize you have better things to do. You think you’ll come back to this website later, but you eventually forget about it.
This happens all the time to Ecommerce and D2C consumers, but for marketers and product growth experts, this is a nightmare to be avoided.
The team at Wakefit was facing the same problem. They noticed that only 73% of consumers were moving from the login page to the next page during the checkout flow.
Checkout was a crucial flow. Consumers already in the checkout process had high purchase intent and no reason to drop off. This led to a lot of potential revenue being lost.
The team doubled down to understand what made customers drop off from a high-intent checkout flow. They realized that the time to convert from the login stage to the password entering stage was 2X the stipulated time. Customers were taking too long to enter their passwords, and they eventually dropped off.
The team introduced an OTP-based sign-up process linked to the customer’s phone number to curb this.
The time to convert for this stage of the process reduced by 100%. Customers were moving faster from one step to another. Correspondingly, conversion rates increased for the core checkout flow, jumping up from 73% to 84%.
It’s not easy to convince the design and product teams to change a process as important as the checkout journey, but data doesn’t lie. The results of Funnel Analysis came in handy when stakeholders needed to be convinced. The team was confident enough to deploy this change — and witnessed correspondingly great results.
This also gave them an opportunity to introduce WhatsApp-based logins, which opened up a whole new channel of communication. The numbers for this are exciting, and the team is looking forward to exploring this in detail.
|Read ➢ How Empiricus Increased Conversions by 45% With User Path Analysis.|
“MoEngage helped us get visibility into how the customer interacts with our website and platform, their behavior and buying patterns, and how they move along the funnel.”
– Abhishek Mishra, Senior Product Manager, Wakefit
Insights are at the core of every decision taken at Wakefit. As a practice, the team leverages insights-led engagement to understand why a problem arises, what causes it, and how it can potentially be solved.
In this data story, we uncovered how Behavior Analysis helped Wakefit boost sales for a new product by 70%. We also discovered how Wakefit increased revenue from the recommendation widget by 2X, and improved the sign-up flow to reduce drop-offs.
By leveraging a combination of Behavior and Funnel Analysis, the Wakefit team was able to crack core problems of discoverability, engagement, and conversions, creating the perfect recipe for product-led growth.
Get in touch today to understand how this can work for you.
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