Distil, a business intelligence start-up in Exeter in the UK, worked with Mancave, which makes natural personal care products, to help it overcome the challenge of customer data in a multichannel e-commerce and retail purchase journey. Mancave has seen a 216% uplift in sales of a cornerstone product, a 21% reduction in customer acquisition cost and a 75% decrease in time to a second purchase.
The challenge of multichannel customer data
Understanding who your customers are is the very foundation of a successful direct-to-consumer (DTC) brand. But as customer journeys become more fragmented with data scattered across multiple channels and platforms, it’s tough to get a holistic view of all the touchpoints.
The team at Mancave wanted to know more about its customers’ buying habits, the marketing channels they engaged with and the role played by both physical stores and third party retailers in their journey.
It was about to undertake a strategic shift that aligned with its goal to grow its DTC Shopify store revenue profitably and sustainably, so the timing was crucial. Ultimately, the team needed to understand what keeps customers coming back.
Mancave brand vitals
Mancave is a natural, performance-led personal care brand featuring products that deliver lasting care to the skin, hair, body and mind.
Part of Aimtru brands, the Mancave range of products contain natural ingredients, premium fragrances and are vegan and cruelty-free.
Mancave products are stocked by retailers and supermarkets and are sold in store and online. E-commerce channels include Amazon and DTC brand store on Shopify.
Challenge #1 – Who are our customers?
Mancave products can be found on the physical and digital shelves of retailers and supermarkets like Ocado, Tesco, Waitrose and Boots, and of course, Amazon. As a growing multichannel brand, customer data is key to a sustainable growth strategy, and the Mancave DTC Shopify store is at the centre of understanding customer behaviour and buying habits.
The Mancave team knew they didn’t want to create a high volume, high churn situation, but instead cultivate a cohort of loyal brand advocates with a high lifetime value (LTV) and repeat purchase potential. The COVID trading years had caused a big shift in popular products, location of sale and marketing performance. So, the challenge was to find its own ‘new normal’ and understand who its new customer cohort really are and it matches its ideal customer profile.
How Distil delivers detailed customer insights
A rich vein of customer data collected from orders, interactions on the Shopify store and engagement on the Mancave marketing channels were all brought together into Distil’s AI-powered Single Customer View, ready for investigation and analysis. Duplicate customer profiles were unified through identity resolution, and customer datasets that were previously disconnected became a holistic single source of truth.
AI-driven customer segmentation
Mancave knew its core customer was likely male, but what about gift purchasers, or family purchases? Customers to the DTC store were segmented using Distil’s AI generated tags, which instantly picked out cohorts of customers who were high value vs low value, those who are loyal to the brand vs those who were at risk of churn.
Geographic location and proximity to store
The team was keen to uncover more about the role of the in-store retail locations in the customer lifecycle and buying journey. With a list of postcodes of in-store retailers in the UK, Distil was able to overlay that onto the location of purchases made through the DTC store to see if there was a correlation between the distance from a retail location and DTC online purchases.
Georgi Grogan, Co-founder of Mancave, said: “Every piece of data is so important to us. As a small team, we need to maximise the return on our time and resources.”
Challenge #2 – Is our marketing hitting the mark?
No brand is immune from default attribution models that favour the platform they are based in. However, relying on these creates a skewed picture of how well marketing channels are performing. Last click attribution has been the simple and easy perspective of attributing sales to marketing channels for some time. Similarly, some platforms even claim sales generated from first click engagements as entirely their own. But neither give the most holistic version of marketing channel performance, and there is a better option.
Opening the black box of marketing attribution
The team was grabbing manual reports from each marketing platform and trying to create a consistent view of performance using this data, but they knew there had to be a better way. How could they see a true reflection of performance by channel? The answer – use an attribution model that makes more commercial sense
Linear attribution model
Distil’s 30-day linear attribution model meant the team could go beyond last click or first click analysis and overcome platform bias in their reporting. They saw the effectiveness of every single channel in this complex customer journey.
Distil’s tracking tag
Making use of behavioural signals picked up by Distil’s proprietary tracking tag, the Mancave team was able to capture users moving from their marketing to their store and all the on-site interactions after that. Having a consistent unique identifier meant the team was able to get a view of its new and returning customers from a marketing perspective, not just an order perspective for the first time.
Grogan said: “I would definitely recommend Distil. It’s been very informative for us from tweaking and fine tuning to reaffirming our strategic thinking and testing hypotheses.”
Challenge #3 – How can we tell if our new marketing strategy is working?
Cue the next phase of the brand’s growth and it was ready to switch up its marketing strategy, but it was a big risk. What if return on ad spend (ROAS) was less efficient or channel performance is reduced? It meant a high potential impact across all teams with bottom-line revenue at stake.
The big change happened in February 2023 – the new brand and marketing strategy was launched. With Distil’s custom analytics and AI-driven customer data platform (CDP), the team felt confident it would see the outcomes of the strategic shift instantly and could pivot if necessary. The key assessment was to understand any differences between the two cohorts and create actionable insights in order to drive profitable growth.
Identifying the newly acquired customers
Having already worked with Distil for several months at this point, it was easy to identify the new cohort of customers arriving after this date. Customers first seen before January 31 and customers first seen after February 1 were divided into two custom segments and using Distil’s custom analytics, performance between both cohorts was analysed. Using the Distil CDP, customers were also further segmented based on a variety of conditions, such as attribution channel, number of products purchased and engagement levels.
Dive into product sales performance
Beneath the waves of this change in strategic direction, the impact on product performance could not be more pronounced. Items in the higher value, personal care part of the range became mainstays of customer baskets, with entry level products losing their previous podium position. It was clear that customer intent was to spend money where it mattered most. As a result, and supporting the original hypothesis, customer spending habits evolved as market conditions became challenging (cost of living crisis). The new cohort chose to spend money on considered purchases such as high-quality personal care items and purchased fewer everyday essentials.
Eyes open on ROAS
It became clear that during this strategic shift, some marketing channels were showing their true colours. Paid search dominated as a high-intent channel, with customers knowing what they wanted, they purchased products that solved a problem. Speculative channels, such as social, didn’t demonstrate such a strong return on investment. The most interesting result is that customers are continuing to repurchase (sooner than they had previously) via paid media ads. For example, analysis discovered that 44% of customers use paid search for their first purchase and 35% of those then continue to use paid search as their most frequent channel, repurchasing sooner than they had previously.
Surface the real impact on Customer Lifetime Value (CLTV)
Whilst acquiring customers is important, so is understanding how long they will stay loyal. By comparing the lifetime value of customer cohorts before and after the strategic shift, it was clear that newly acquired customers displayed a greater LTV. A positive sign for Mancave’s marketing team and key to its DTC scaling plans. By having a clear, accurate picture of the customer acquisition cost and lifetime value, the team could confidently assign budget to different marketing channels knowing what their likely return would be.
“By using Distil to compare performance across two different cohorts, we’ve been able to assist Mancave with its decision making. By interrogating granular data, we have given confidence in its marketing strategy, but also unearthed actionable insight for further refinement and iteration, a key to unlock future growth,” said Matt Abbott, E-commerce Data Specialist.
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