Why Data is the Secret Weapon for DTC Brands

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As many retail brands race to catch up with digitalization, direct to consumer (DTC) players are raking in the chips. The explosion of connected devices and channels has given them multiple pathways to take offerings straight to consumers, cutting complexity and costs.

But while streamlined sales and distribution processes are increasingly popular – with more than one fifth (22%) of consumers set to go direct for 40-59% of buys by 2023 – DTC brands could be making more of their unique position. Unlike traditional retailers, they have total control over how their products are sold and a first-hand window into shopper activity.



To make the jump from market disruptors to dominators, DTC brands must start harnessing the data at their fingertips to deliver experiences that set them further apart.

1. Making experiences personal

It’s not news that shifting consumer habits are changing retail. Not only is rising appetite for online shopping driving brands to increase their digital presence, but increasing demands have also raised the experience bar; with 73% of consumers expecting brands to understand their individual needs. And DTC brands are ideally placed to meet this demand.

With full ownership of the path to purchase comes detailed insight into every consumer interaction. DTC players know when, where and how consumers engage with their brands, and the effect of each touchpoint. In other words, they have the information necessary to power ultimate personalization, as long as they take the right approach. Past research shows that simply being on first name terms with consumers isn’t enough; if DTC brands want to build relationships that fuel lasting loyalty and sales, they must provide truly personal value.

When it comes to marketing, that might include bespoke retargeting with discounts based on previous buys or tailored promotions for new customers. See, for instance, wine subscription brand Winc, which tracks data about orders and customer responses to constantly refine recommendations, and adjust the wine it develops. For services, DTC brands can combine smart technology and data to drive convenience; using tools such as chatbots — a particular favorite with millennials — to quickly solve queries, track orders, and make suggestions that align with specific preferences.

2. Easing multi-channel transitions



It fits with the nature of convoluted modern shopping that consumer behavior has also pushed web retailers towards offline. Though many DTC brands found their initial success online, they have discovered that catering to multi-channel consumers calls for real-world purchase points too. Sustainable clothing company Everlane, for example, has gone from ecommerce-only to testing a pop-up shop and then a permanent physical store, and it’s much the same story for lifestyle luggage brand Away — with stores now boosting its web traffic.

Ensuring optimal consumer satisfaction, however, takes more than just flexible buying options; each step of omni-channel journeys must add up to a positive and seamless overall experience. And that’s where effective data usage comes in. At a basic level, that may involve recording individual details in organization-wide customer relationship management systems (CRMs); making it possible for saved logins, settings or payment information to be quickly retrieved and used across mobile, desktop, or connected in-store screens.

Moving up a gear, DTC brands can leverage tech capable of harnessing machine learning (ML) to power informed decisions and deeper relevance. For example, advanced dynamic creative optimization (DCO) platforms can help analyze data from multiple sources and put it into immediate action: establishing which messages and formats work best for individuals, and instantly adapting communications to match current needs, interests, and channel of choice.

3. Predicting future needs

Retail has always involved an element of future-gazing; measuring sales, seasonal patterns and emerging trends to guide planning. But in today’s fast-moving competitive market, going beyond that to precisely predict what consumers are likely to want is vital. Whether or not DTC brands specialise in one particular product, they still need to deliver ads or promotions at just the right time – and in the right way – to make a positive impact.

Once more, data has an important role to play. By utilizing the large-scale processing ability of ML to assess data about historic consumer purchases, ad responses and cross-channel engagement, brands can anticipate, and accommodate, their next move in real time. Plus, with subsets of ML that can find the ideal course of action in any given context – such as reinforced learning (RL) – they can even set algorithms to identify which type of ad will achieve specific key performance indicators (KPIs). For instance, say the goal is increasing conversions and the customer has viewed multiple product videos on mobile before buying via desktop in the past. Chances are high that serving a personalized ad when that customer returns to the desktop site will be successful in encouraging them along the funnel. And as an extra bonus, the more often RL algorithms accomplish their mission, the more accurate their choices become; consistently optimising message delivery and budget allocation.



DTC brands are already turning the retail revolution to their advantage; wielding the ever-rising number of digital platforms to gain vast exposure and audiences. But relatively few have tapped their greatest asset. By blending valuable first-party data with sophisticated tech that can extract the insights it contains, DTC brands can significantly accelerate their current momentum; not just identifying how and where experiences could be improved, but also which steps they can take to ensure future efforts deliver better results.

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