In retail, clienteling has everything to gain from data quality
A regular customer is worth more than a one-time buyer! More than ever, in an especially competitive environment, retailers must both build customer loyalty, and stand out from the competition. Clienteling is one of the best ways to turn every interaction into satisfaction chance to delight your customers, provided it is based on customer information that is accurate and reliable. Data quality plays a vital role here. Validated customer data strengthens the personal connection with each individual customer.
Data quality: a key ingredient of clienteling in retail
In the one-to-one clienteling relationship, knowing and recognizing each customer is essential, as is anticipating their expectations. Yet there are no usable customer insights without complete and verified data. In retail, data is collected through multiple channels, such as stores, websites, mobile apps, social media, and chatbots. Data quality secures two key stages of clienteling by ensuring consistency across all sources:
Identifying customers: While fundamental to any personalized customer relationship, customer identification can quickly become unreliable due to duplicate records, variations in the spelling of names, or outdated or incorrectly entered contact details. This highlights the importance of ensuring the reliability of identification and contact data – first name, last name, title, mailing address, active email, up-to-date landline and mobile numbers, etc., from the moment it is collected.
Knowing and targeting customers: Whether through their preferences, habits, or purchasing criteria, understanding each customer’s buying profile requires bringing together data that is complete and accurate. Data quality makes this qualification possible. And an additional benefit, it provides fine-grained segmentation capabilities based on purchasing behavior, brand interactions, and sociological data.
Without data quality, clienteling efforts are undermined by inaccurate and unreliable data. Retailers may experience the following issues:
- Cumbersome data entry steps: whether online or in-store, lengthy and tedious forms without automation can be frustrating. They are likely to introduce errors into the data meant to support clienteling efforts.
- Bounces and undelivered packages: how can a lasting relationship be maintained if communications and deliveries don’t reach their destination? Incorrect contact details are often the reason emails and packages don’t reach customers, with email errors alone accounting for 20% of delivery failures in e-commerce (MetaPack).
- Duplicates: multiple copies of communications, duplicate mailings and catalogs sent to the same address are all signs of duplicate entries in the database. Loyalty programs also suffer from duplicates in retail. If a customer exists under several contact records in the database, their purchase history becomes fragmented, undermining the tracking of loyalty points. Watch out, 19% of companies lose a customer due to the proliferation of duplicate records in their database (Ecommerce News).
Unqualified customer data leads to situations that go against the goals of clienteling. It makes perfect sense for retailers to integrate data quality into their customer data processing to avoid these pitfalls.
DQ's capabilities serving retailers
Qualifying and deduplicating customer data is essential, but how does managing customer data quality specifically support clienteling in retail?
In terms of customer experience, from the moment of input: autocomplete on forms ensures reliable input and makes the task easier. Data quality can also trigger an alert for in-store advisors if the customer already exists in the database. This prevents creating a duplicate, and the existing record can be updated in real time. It’s also an opportunity to verify the accuracy of the data that has already been entered. The benefit is immediate, without any tedious effort on the form. In the longer term, the relationship with the customer improves: they are known, recognized, and contacted using the correct details.
In terms of relationship quality: eliminating duplicates helps consolidate purchase history, preferences, and interactions, which are all key elements for delivering personalized service. Loyalty programs are better managed and free of errors. Deduplication and autocomplete thus prove to be prerequisites for any successful clienteling strategy.
In terms of customer segmentation: data quality enables segmentation based on postal address, dividing customers into dozens of segments with their own specific characteristics, interests, and consumption behaviors. Thanks to this data-driven approach, retailers can enrich the 360° view of each customer and better tailor their marketing actions to preferred communication channels. In terms of products, it becomes easier to highlight items that meet various criteria, such as “Made in France” labels, CSR, sustainability, etc. Lastly, this segmentation helps adjust the offer, pricing, and level of promotion according to the customer profile and the brand’s positioning.
Clienteling that is finely tuned all the way to the sale
At DQE, retail clients confirm the crucial role of data quality in their clienteling operations.
They value the ability to enrich customer knowledge and consolidate a 360° view:
At Madura, Paul Valton, E-commerce Manager, explained:
“Following the batch cleansing of our databases, our data is clean. Our single customer view has improved. This boosts the performance of our marketing and CRM actions.”
The retailer Pacific Pêche shared the same positive reaction:
“DQE’s solutions allow us to better understand our customers through their data. This is a key to Pacific Pêche’s success in making the shift to omnichannel and running segmented, profitable email campaigns.”
Hess Automobile has also made great strides in customer insight. The group was able to implement deduplication that meets the requirements of its business – for example, recognizing members of the same household, or employees of the same company, regardless of their points of contact with Hess Automobile.
Input help is transforming the customer experience for many retailers:
Bureau Vallée is one of them. Soizic Poirier, Digital Transformation Project Manager, speaks of a “real time saver when entering customer contact details”. Indeed, a customer record is filled out in the store four times faster than before. Data quality eliminates two other major pain points in customer relations: undeliverable packages and email errors. “By using DQE for qualifying postal addresses as soon as they are input, we see a marked improvement in deliveries and a decrease in complaints transmitted to our customer service department. This of course improves the customer experience, since they receive their orders quickly, and at the correct address,” reported Philippe Tonnellier, IS Manager at Au Forum du Bâtiment.
Retailers use data quality to boost clienteling all the way through to the sale:
On the one hand, when input help makes the form-filling step smoother, the conversion rate tends to increase. Charles Nicolas, E-Commerce and Digital Transformation Lead at Royal Canin, confirmed this: “With DQE, input help for postal addresses has reduced the time our customers spend on the Royal Canin website form by 20%. This results in a better experience at this strategic step in the purchase funnel and a 5% increase in the conversion rate.”
The online fashion site Justfab also confirms a smoother and more intuitive purchase journey, with a 45% decrease in cart abandonment at the address entry stage.
On the other hand, email validation ensures a deliverability rate close to 100%. In targeted and personalized campaigns at the heart of clienteling, this deliverability enhances customer satisfaction, which in turn leads to higher opening and conversion rates. This is the case, among others, at IZAC: “DQE provides us with unified and qualified customer data, a prerequisite for applying our targeting rules to a controlled database. Our emailing campaigns have now improved in deliverability with a rate of 99%, but also a better opening rate” explained Victoire Lausdat, Director of CRM.
DataQ allows you to control customer data (B2C and B2B) at every collection point, in real time and in batch cleansing mode. Discover the 8 modules dedicated to data optimization: postal address, email address, phone numbers, title, and legal entity data.
Unify is a solution dedicated to the deduplication and merging of your customer databases. It provides a 360° view of your customers.
About DQE
Because data quality is essential to customer knowledge and the construction of a lasting relationship, since 2008, DQE has provided its clients with innovative and comprehensive solutions that facilitate the collection of reliable data.
17
Years of
expertise
800
Clients in all
sectors
3Bn
Queries per
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