Within the retail sector, going direct-to-consumer (D2C) has become increasingly popular among big brands, and there is no sign of this trend slowing down, and why would it? After all, it allows retailers and manufacturers to move away from working with channel partners, thereby giving them complete control of the end-to-end consumer experience, as well as more agility, opportunities to innovate, and increased revenue.
In recent years, the emergence of more D2C brands, such as Glossier and Made.com, has demonstrated just how successful this model can be. Nowadays, 55% of consumers prefer to buy from brands directly, while 82% of consumers currently have up to four D2C relationships – showing there is room for growth.
Yet, with the considerable benefits of a D2C model come significant responsibilities. According to research from The Drum, 94% of consumers cite “convenience” or “ease of use” as the top benefits of D2C brands. Other drivers of shopping with them include “control over my purchases” and “the ability to customise”. As such, D2C brands can’t afford to drop the ball – they need to consistently answer consumer demand and meet their expectations for these types of services and interactions. Not only does this require brands or retailers to supply the right products, in the right quantities, but they also need to do it as quickly as channel partners have been able to and engage with consumers in the ways they desire. Ultimately, to compete at this level, retailers must look to their data.
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The current barriers to going D2C
Data is central to successful D2C businesses. However, to use it to power their success, the majority of retailers first need to get their data in order. Like businesses across all sectors, retailers are often faced with data silos which inhibit their ability to leverage the wealth of volume they have available, ranging from which products are most popular in which locations, to how many of each product is currently in stock. At the heart of this problem tends to be a data architecture made up of multiple different technologies, many of which are likely to be based on legacy systems. This makes it difficult for brands to access, share, and integrate data.
This can mean brands aren’t able to gain a real-time view of stock levels and find it difficult to accurately forecast demand, both of which are vital if they are to adopt a D2C model. On top of this, collating data from across all stores and channels to obtain a joined-up picture of their entire operations, as well as using it to make informed and intelligent decisions, is at times impossible.
Unsurprisingly, this has a knock-on effect. It can make providing customers with the right types of experiences and ensuring they have the right products available in the right stores extremely challenging. And, at a time when consumers are increasingly expecting more personalised interactions with brands and retailers, being unable to leverage data to gain a 360-degree view of customers could mean losing out to better-positioned competitors.
Therefore, removing data silos and finding ways to integrate and share data across the entire ecosystem, both online and instore, is vital to gain the holistic view needed to both successfully shift to a D2C model and keep pace with consumer expectations. This is where data fabrics, a new type of data management architecture, can be of significant value.
Finding a path forward with smart data fabrics
Data fabrics offer organisations, both within and outside the retail sector, centralised access and a single, unified view of data across their entire enterprise. This can be taken one step further with the use of ‘smart’ data fabrics, which embed a wide range of analytics capabilities, making it faster and easier for brands and retailers to gain new insights and power intelligent predictive and prescriptive services and applications.
For retail organisations reluctant to replace siloed systems due to the expectation that the cost would be prohibitive, smart data fabrics mark a way for them to continue to leverage their existing investments by allowing existing legacy applications and data to remain in place. This means enterprises can bridge legacy and modern infrastructure without having to “rip-and-replace” any of their existing technology.
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Harnessing data to drive D2C initiatives
When it comes to adopting a D2C model, this approach will allow brands and retailers to harness data from across their different channels to better understand their customers. This will empower them to provide the right types of experiences and interactions and to gain a more informed understanding of the types of products their customers desire, for example.
Additionally, having access to real-time data can help D2C retailers in areas such as demand planning and in the supply chain. Currently, the majority of retail organisations use different versions of same systems in different locations. As such, they don’t tend to have a proper view on stock levels, manufacturing capacity, and when shipments will arrive, for example – making planning difficult. By implementing a smart data fabric, these businesses can obtain the knitted together view of what is happening across the board within their brand needed to more accurately plan and forecast, and ensure they have the right inventory to match.
Capitalising on a new opportunity
For brands, both new and legacy, shifting to a D2C model offers significant opportunities to adapt to the changing way in which consumers like to shop and to establish themselves in their own rights, rather than operating through channel partners. As more brands embark on this journey, ensuring they have the architecture to turn their valuable data into insights to deliver the products and experiences desired by their customers will be vital. Armed with this intelligence, brands will be better positioned to make it on their own and reap the rewards of a D2C model.
