Oct 2021 | Data Quality

What is location intelligence and why is it critical to retailers today?

As online shopping continues to grow, retailers and logistics companies are under increasing pressure to reach the customers’ front door, first time and every time. Having a valid postal address for a customer is the starting point but this often isn’t accurate enough to ensure a smooth and efficient delivery.

According to Experian’s 2021 Global Data Management Report, 95% of the organisations see negative impacts from poor data quality and a third of the organisations believe that poor quality data damages their customer experience and their reputation with customers. With more deliveries than ever before and more new delivery drivers on the road, retailers and logistics companies need to remain one step ahead, using the latest address validation and cleansing technology and data available to drive business efficiencies and meet their customers’ increasingly high expectations.

Watch this webinar, led by Experian’s Data Quality Product and Consultancy experts, you’ll hear:

  • The typical delivery headaches retailers face today
  • Latest insights from Experian’s global data management research
  • The importance of address validation with location insight to retails today
  • How Experian’s solutions can help to maximise delivery rates

 

Speakers:

 

Natalie Jones Lewis Cameron Wallace Brown
Natalie Jones
Global Product Marketing Manager		 Lewis Cameron
Account Director & Team Lead, Retail		 Wallace Brown
Senior Consultant


Loading...

Watch this webinar

By signing up to Experian business marketing communications you will receive the latest research, insight, news and invites to events and webinars. Experian offers a wide range of products and services. We will do our best to send you only communications that we deem to be relevant to you, your job and your business. You can change your mind at any time.


View our Privacy Policy for details on use and storage of your personal data.

*Denotes a required field