With an average website visitor conversion rate of just 3%, retailers struggle to convert sales. Online retailers lose an estimated $18 billion in revenue annually due to last-minute cart abandonment. Remarketing, the use of real-time insights to provide targeted recommendations, is just one effective big data methodology that can yield a 55% increase in spend from cart abandoners.
Few industries are more impacted by quickly-changing consumer trends than retail. The complexity of consumer preferences means that big data is especially promising and differentiating for organizations in this sector, according to IBM’s Rebecca Shockley and Keith Mercier. In a retail environment where consumers take a multi-channel approach to product selection and purchase, creating a 360-degree view of target customers is particularly critical to retaining business.
62 percent of retailers report that increased adoption of analytics is creating a competitive advantage. While retail adoption of third-party data actually lags slightly behind other industries, retailers who optimize for modern cross-channel shoppers are likely to gain an immense lead. In this article, we’ll explore some ways that modern retailers are utilizing big data insights to understand cross-channel behaviors and create a targeted customer experience.
Understanding Modern Cross-Channel Shoppers
Retailers are struggling to create complete pictures of today’s multi-channel customers, according to eMarketer. 35% of marketers report they just don’t understand a customer’s journey. Retail companies struggle to understand how customers behave on mobile, desktops, and at brick-and-mortar locations. In an age where over 40% of adults are multi-screen users, fragmented or incomplete data insights can severely inhibit effective targeting.
The BDEX Data Exchange Platform (DXP) can assist retailers in understanding the customer’s journey, even if their product research takes place across multiple channels or devices. Customer behavioral data, first and third-party transactional insights, and even online product reviews can facilitate a multivariate understanding of what is most likely to convert. With access to a wide array of insights, retailers can gain the right insights to correctly target consumers the first time they land on a website.
Retailers are increasingly discovering that analytics, given access to the right third-party data insights via the Data Exchange Platform, can be a powerful tool for understanding complex consumer behaviors. Retail optimization has always been a complex science, but being able to incorporate a broader range of data sets can allow marketers to finally uncover a complete picture of customer behaviors.
Predicting the preferences and needs of consumers is a challenge across industries, from entertainment to retail. Big data evangelist James Kobielus describes the complexity of modeling the quicksilver nature of human preferences, or zeitgeist, due to the fickleness of taste. Retailers are especially well situated to utilize experience analytics to predict how demographic preferences can change, and target offers accordingly.
Three examples of experience analytics relevant to retail include:
- Life-event detection: The detection of marriage, pregnancy, or other events that can drastically change retail habits via analysis of behavioral and identity data.
- Behavioral pricing: Using a combination of consumer transaction history, behavior, and other qualitative insights to predict deals that are most likely to elicit a positive response.
- Psycholinguistic Analytics: An algorithm which works to detect patterns in human language and social media behavior to uncover probable consumer preferences.
For retailers to achieve success with any analytics project or initiative, obtaining sufficient third-party insights is crucial. Without identity, descriptive, qualitative, and quantitative data insights, retail analytics teams will be unable to uncover sufficient patterns to predict purchase behavior and target offers. The retailers today who gain a significant edge on their competitors are those with the ability to procure enough accurate and recent third-party insights on their target markets.
The Data Exchange Platform (DXP) provides retailers with the ability to purchase minutes-old insights on the right consumers, creating a rich understanding of who they’re trying to sell to. Consumer behavior is complex, and data exchange can be a powerful tool for obtaining the right insights. By purchasing fresh and quality-scored insights in a true marketplace environment, retailers can ensure they’re gaining access to actionable data.
Retail analytics is only as effective as your big data procurement. For more information on the buyer benefits associated with the BDEX Data Exchange Platform, check out Exiting the Black Box Mentality: How the Data Exchange Platform Can Benefit the Buyer.