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Why Digital Analytics Is So Important Today – and Three Real-World Practical Use Cases

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Read more about author Nitin Aggarwal.

The COVID-19 pandemic forced almost every organization to adapt to digital ways of working and operating virtually overnight – no matter their sector. It was a culture shock that meant brands had to accelerate their digital transformation strategies at short notice and push through changes that had been in development or stuck on board agendas for years. 

The change wasn’t just on the company side either – consumers had more digital presence than ever before in 2020, setting digital literacy and comfortability and preference for digital purchasing and interactions at an all-time high. 

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Facilitating that shift so quickly has been a tough job for many companies. But, the good news is that all of that extra digital interaction has helped create a wealth of data that can be used to better understand exactly how to engage with, understand, and sell to their customers in this new digital-first landscape.  

Critically, to get full value from that data, organizations will need more digital and advanced analytics capabilities that consider the entire modern data profile of each customer – measuring data from both digital and physical sources. Those that succeed will be able to create a new 360-degree view of their customers that spans every touchpoint of the relationship. 

Here are three use cases that demonstrate why digital analytics are so valuable and what organizations across industries are using them to achieve today. 

Use Case 1: A Consumer Goods Organization Optimizes Its Customer Journeys  

This wines-and-spirits distributor previously operated on a traditional, salesperson-led approach to customer service – building long-lasting relationships between its sales team and customers. And up until just two years ago, when the company set up its first e-commerce platform, it did all its selling directly through non-digital channels.  

The company has come a long way since its move to digital. And a big part of its success can be attributed to its use of more advanced analytics on its website.   

Now, the company can answer more specific questions about how customers use the individual features of its website, such as search and navigation. These insights help the distributor understand why customers abandon carts and sessions, why specific campaigns aren’t working, and how much revenue and value is generated from platform optimizations and automated product recommendations. 

Equipped with this knowledge, the company can strategically design customer journeys that encourage sales and drive positive user experiences. So far, that insight has helped the company drive a significant year-on-year increase in revenue through both traditional channels and its e-commerce platform. 

Use Case 2: A Large Fashion Retailer Understands Its Customers’ Buying Behavior on a Granular Level 

Black Friday is the biggest – and most competitive – weekend of the year for fashion retailers, so it’s critical that marketing budgets are spent in the most efficient way possible. Like many in the industry, one large U.K. fashion retailer wanted to allocate specific budgets to each of its social platforms. But without an accurate view of its customer preferences and journeys across those platforms and channels, it was difficult to know where to prioritize. 

To solve its challenge, the retailer uses digital analytics to identify where its customers are and create an accurate view of their buying journeys. The insights reveal granular details about customer behavior, including their movement and interaction across multiple channels up until the point of purchase.  

For example, if an ad on a social platform influences a customer to purchase, but they complete the purchase by typing in the brand’s URL, the retailer can still credit the ad as the main influence for the sale.  

Insights like these help the retailer identify which channels and marketing methods truly work for the brand, and which the team should focus on in the lead-up to Black Friday – ultimately generating more value from its marketing budget. 

Use Case 3: A Leading Beauty Retailer and Pharmacy Chain Creates Highly Personalized Shopping Experiences for Its Customers 

Delivering standout customer service isn’t just about making the buying experience effortless – it’s also about designing satisfying website experiences. This idea has always been a priority for one of the U.K.’s leading beauty retail and pharmacy chains, and it used digital analytics to take its experiences to another level. 

The brand used its customer data to create highly personalized experiences for its website visitors, producing tailored homepages with customized content. This content goes beyond traditional, personalized product offerings by showing customers unique banners based on their previous browsing behavior and preferences. 

The insights the brand generates from its customer data allow it to create effective campaigns that encourage customer loyalty, keep customers on the website, and generate more sales. Plus, it offers accurate indicators on where the brand can optimize its website to further improve visitor retention. 

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