Redefining your customer data strategy for amazing results
New research shows how companies are taking a more comprehensive and customer-centric approach to customer data with an eye on a big payoff.
If retailers learned anything from the holidays, it’s that data-driven decision-making must be a priority in order to achieve their goals for 2023 and beyond.
The numbers point to an unpredictable future.
On one hand, the National Retail Federation expected 2022 holiday retail sales to grow between 6% and 8% over 2021, which would break records if that prediction holds once all the numbers are tallied.
In addition, the labor market in the U.S. remains strong and COVID-19 restrictions have eased.
On the other hand, economic indicators are increasingly pointing to a recession, credit card balances are rising, and geopolitical turmoil continues.
Despite this challenging environment, retailers that take a fresh approach to data can boost customer loyalty and their bottom line.
Enterprise, meet your customer.
Interactions, data, front and back office – connected.
It starts here.
Data-driven decision-making: Connecting the puzzle pieces
The pandemic highlighted a cold truth for retailers:
Back-office processes often dictate CX.
Supply chain disruptions lead to delayed shipments.
Inventory shortages lead to unfulfilled orders.
And staffing issues cause massive wait times at call centers.
All these situations pose a crucial question: Which customers deserve priority?
Unfortunately, none of the systems that manage back-office processes give insight into customer context. Who are the profitable customers versus those who return many of their orders? Who are the social influencers? Who are the churn risks?
Front-end engagement systems complete the picture:
- Marketing systems show the promotion that attracted the shopper
- E-commerce solutions show who made online orders
- Experience management reveals customer sentiment via survey data
- Service records show who’s most likely to call for order updates.
When all this data is stored in separate systems, it’s hard to make sense of it. But if it’s assembled in one unified view, retailers can make informed, data-driven decisions that lead to higher profits, more efficient use of resources, and elevated brand reputation.
In an interview on retail data strategy, Brad Blackmon, Executive Vice President for Publicis Groupe, said: “We’re at this perfect time now where technology and data are at a level where real-time decisions can happen.”
Proactive customer experience: How a CDP can help end bad CX
Creating better, proactive customer experience is the next phase of customer data management as brands connect CDPs to back-office ERP systems.
Retail data strategy: All together now
To create a unified view of the customer that enables real-time business decisions, leading businesses are developing centralized data models. These unified models help them expose customer data to processes and applications across the enterprise.
A 2022 survey by HBR Analytic Services, in association with SAP, asked more than 180 businesses – including many retailers – about their data strategies.
Nearly 4 out of every 5 respondents said they’d implemented a centralized data model, were amid an implementation process, or had plans to do so.
One key output of a centralized data model is an accurate lifetime value score for customers (CLTV). This metric helps retailers make decisions that positively impact the bottom line.
“Brands can use data smartly to cross-sell and upsell when the chance arises,” Blackmon said. “They can also use it to focus less on those consumers who may not be as valuable, and instead reward those loyal customers.”
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Top 3 examples of data-driven retail use cases
Here are three examples of how a unified customer view based on a centralized data model can benefit a retail strategy:
- Reducing pain points in returns processes
- Unifying enterprise and customer data to reduce and eliminate churn
- Improving service and customer sentiment
1. Reducing returns pain
Serial returning, also known as “bracketing,” is the act of purchasing multiple versions of an item and returning most of them. One study found 63%of shoppers admitted to bracketing, up from 55% in 2019.
The practice clearly damages retail revenue. Unpacking, processing, and item inspection of returns make them a drain on time and resources. They also take up valuable space in fulfillment centers; and if those facilities reach capacity, the retailer can’t bring in new inventory.
With a complete understanding of customer profiles, brands can segment bracketers into campaigns limited to in-store promotions. They can also target the more profitable customers with online promotions and deals to strengthen their loyalty.
2. Stopping churn before it starts
Delayed orders and missed deliveries wreak havoc on customer loyalty.
In one recent survey, more than 35% of consumers said they switch retailers after a negative delivery experience and write a negative review or social media post.
With a clear view of supply chain data and order status as part of a unified customer profile, retailers can identify the high CLTV customers with late orders and take proactive measures.
For example, they can offer these customers a discount coupon for their next orders. They can also prioritize these customers when they call a contact center, so long wait times don’t compound their frustration.
3. Raising customer recovery rates
It’s no secret that consumers complain more and treat retail workers poorly during the holidays. With an improved understanding of customer data, however, brands can prioritize complaints and focus on profitable customers.
With an up-to-date view of customers’ purchase history data, for example, brands can see who has continued purchasing goods or services after their complaints. If a high-value customer has cut off engagement since the complaint, the brand can push them into a cross-channel campaign for recovery.
In addition, it can activate a ticket in a call center so an agent can follow up on the complaint status.
CDPs for retail: Build vs. buy considerations
When researching customer data platforms (CDPs), retail brands often wonder if they should build or buy the solution from a vendor. We're breaking down the considerations in this post.
Data management for retail resilience
For many retailers, siloed data is a problem. It prevents them from identifying high-value customers in in critical buying moments and taking action to strengthen their loyalty.
Data-driven decision-making in retail can improve customer experience and sentiment, while also strengthening the bottom line.
By prioritizing data-driven decision-making, retailers can solve this challenge, improve their customer experience, operate with more efficiency, and take positive steps toward their financial goals.
