Francesca's offers hand-picked, carefully curated eclectic clothing, bright baubles, bold accessories and playful gifts for women. Founded as a single boutique in 1999, Francesca’s now boasts more than 700 boutiques across the country, plus an online boutique that was launched in 2006.
Francesca’s had a single mission — to surprise and delight every customer every time, on every channel. But making this happen was difficult because they didn’t know exactly who their customer was. While the company had a grasp on customers in general — they knew, for example, that she was likely between 18-35, fashion-conscious, crazy about pets and apt to follow trends — they didn’t have a granular view of specific customers. Francesca’s quickly realized that in order to more effectively communicate with customers, they needed to know more about them as individuals.
Because Francesca’s was engaging customers across multiple channels, it was generating a plethora of data points — one-off bits of information like an email address collected in one channel, an SMS phone number collected in another, and an account created on the e-commerce site. This meant that one customer could have multiple records with different associated emails and phone numbers. But what Francesca’s couldn’t do was aggregate that data to create a single, unified view of the customer at a granular level. With millions of records, it was clear that Francesca’s needed a way to bring order from chaos. \
After reviewing other CDP solutions — and implementing a more robust POS system that facilitated in-store data collection — Francesca’s partnered with Acquia’s AgilOne to integrate its disparate data points in a way that would allow them to take action. Breaking down these data silos gave Francesca’s a number of “aha” moments. It helped them effectively calculate a particular customer’s lifetime value — giving them insights into how the lifetime value of a customer whose first purchase was a dress differed from a customer whose first purchase was accessories — and helped drive decisions about which categories they choose to leverage during customer acquisition campaigns.
AgilOne also allowed Francesca’s to identify, across channels, the top 10% of its customers. This made it possible for the company to build lookalike models off of its most valuable customers while recalibrating their expectations about acquisition costs. Additionally, insights about customers’ price sensitivity helped Francesca’s determine if a particular customer would be more likely to respond to a clearance offer versus a full price “new trends” offer, helping them tailor campaigns.
Francesca’s now has a deeper sense of their individual customers, better understanding her lifetime value and letting that information inform their new customer acquisition spending. Additionally, they are able to analyze omnichannel customer data at a macro level, identifying factors like differences in average lifetime value among customers acquired via different product categories. This helps Francesca’s determine not only what categories to lead with for customer acquisition campaigns but also provides a roadmap for finding more of its “ideal” customers.