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Chain of Demand

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How DTC Brands are Leveraging Data

As consumers switch from in-person transactions to e-commerce and adopt new services, the direct-to-consumer business model has risen.

 

In order to grow, personalize, and connect with consumers effectively, DTC brands have utilized data, creating touchpoints that engage the user throughout the purchasing journey. By collecting everything from purchasing history and social media insights to demographic data and feedback forms, DTC brands have successfully created a multilayered approach to understand and connect with many different customer segments.

 

The power of data

The DTC model allows companies to collect information on topics such as consumer demographics, preferences, and behavior throughout the entire purchase journey. This ability to measure all aspects of the value chain is extremely powerful in creating a holistic view of the consumer journey.

 

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DTC e-commerce sites alone allow companies to record crucial data including onsite behavioral analytics, searches, reviews, purchase trends, inquiries, and more. Companies are then able to improve the onsite experience, market effectively, grow engagement, and carry out product development.

 

With more than one-fifth of consumers projected to go direct for between 40-59% of purchases by 2023, it is clear that DTC brands are innovating and connecting with consumers at an increased level. With this insight, it’s worth exploring the ways in which DTC brands have successfully leveraged data to grow.

 

Increase personalization

DTC brands have expanded personalization beyond the usual product recommendations. In doing so, DTC brands have connected with consumers at a closer level, developing one-to-one relationships.

 

A study by Salesforce and Publicis.Sapient found that 64% of shoppers felt like retailers don’t truly know them. Personalization may serve to change this feeling. In fact, Epsilon reported that 80% of consumers are actually more likely to do business with brands that personalize their experience.

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Healthy snack company Graze has excelled in the personalization realm. The company asks customers to share their likes and dislikes and then creates a curated subscription box. After each delivery, customers can give their feedback, which is then used to further personalize their next box. This personalization is, at its core, fueled by data, with Graze’s algorithms using 300 million customer ratings of its products at a rate of 15,000 per hour. Their investment in data has had tangible results, with Graze becoming the UK’s leading food subscription business.

 

Enhanced experiences

DTC has prioritized the experience aspect of shopping, focusing on providing value beyond that of the product itself. Besides convenience, customers are beginning to care more about connecting with a brand and enjoying the shopping process at every stage. According to an article on Forbes discussing successful DTC brands and the actions taken by then, it states that the secret to their successes has largely been attributed to their ability to “make data-driven customer experiences their core offering.”

 

In fact, according to a recent Salesforce report, 62% of consumers surveyed claim to share bad experiences with others, while 72% of consumers say they share good experiences with others. Additionally, 67% say that they would pay more for a good experience.

 

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Popular DTC brand Pura Vida Bracelets has explored this channel, developing its own retail experience called “Sip + Shop”. Partnering with Kombucha brewery June Shine, they hosted a Happy Hour with live music and mural painting, offering a discount for those who purchased from Pura Vida. Likewise, other DTC brands can create similar social shopping experiences, leveraging data to a better position, and market these events.

 

Optimize marketing spend

Data has powered DTC companies to optimize their marketing spend, using digital data collection measures and effective modeling to allocate marketing dollars effectively. The pre-defined models that more traditional retailers use have analytical limitations, however, DTC companies are working past that by tracing marketing spend to the type of purchase made.

 

As e-commerce becomes increasingly popular and digital technologies become more incorporated into the daily lives of consumers, there will be even more room to use data to increase the percentage of traceable marketing spend.

 

Improve product development

Another area where DTC brands have successfully utilized data is in product development. By leveraging sources including direct customer feedback, historical purchase data, and natural language processing on social media comments, DTC brands have made customers an active part of the feedback loop.

 

DTC brand Soylent has utilized data to drive the development and launch of their meal bars. When the meal bars were first launched in 2016, they were not well received, and the company quickly recalled the product. In 2019, they launched the product again, and this time it was a success. What had changed was the way in which Soylent used data to improve the product. Soylent sent out requests for reviews of its meal replacement drinks to existing customers, but many brought up mobility issues and wanted a more portable option. By compiling data from these reviews, Soylent was able to pinpoint problems with their original launch and improve the product line.

 

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Image via Railsware

 

In a similar way, popular DTC companies like Thrive Market and Peleton have Facebook groups where members can ask questions and comment about the products, helping the brands to analyze customer sentiment and collect feedback. Ultimately, using data in these ways helps companies to iteratively improve existing products and make other key product decisions.

 

Inform expansion

Successful DTC brands have also used data to inform company expansion or transition activities. By leveraging the power of analytics, companies have been able to garner what consumer segments are looking for, and therefore increase the adoption of additional company products or platforms.

 

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DTC brand Glossier actually started as Into the Gloss, a blog discussing beauty tips and trends. When they first launched Glossier, the team assumed that readers of the blog would quickly purchase new products, but that wasn’t the case. Glossier and Into the Gloss had to intentionally trace behavioral data between the two platforms in order to better position blog readers as Glossier customers and customers as Into the Gloss readers.

 

Glossier also utilized insights from conversations occurring on Into the Gloss platforms to inform company activity, messaging, product development, and more. Ultimately, Glossier was able to grow extremely fast, becoming a unicorn in 2019 after just four years of operation.

 

Deeper insights into consumer demand

It is evident that the use of data has been instrumental in the success of many DTC companies. As mentioned above, many DTC brands have been able to grow, personalize, and connect with customers effectively by creating a multilayered, data-driven approach.

 

But as more brands continue to grow, they are realizing that data alone is not enough. Learning how to leverage the data effectively, especially during times of recession is what will distinguish the winners in this new landscape of retail. Predictive analytics solutions made by Chain of Demand aims to solve exactly that. Not only does it help to provide deeper insights into their inventory, it can help upcoming DTC brands act on consumer demand quicker than their competitors.

 

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