How to Personalize the Retail Experience with Data


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How to Personalize the Retail Experience with Data

Leading retailers have made great strides in becoming omni-channel, multi-channel marketing experts. Reaching consumers across multiple channels, having a strong digital presence, engaging on social platforms, and embracing mobile continue to be key themes in targeting today’s shopper. However, being present across a myriad of channels is no longer enough to entice consumers who expect more from brands. Consumers want and demand personalized communications if they are to give up their hard-earned dollars.

Consumers expect retailers to know their preferences and interests. A recent Infosys survey reported that 78% of consumers are more likely to be a repeat customer if a retailer provides them with targeted, personalized offers. And if a consumer does not receive a personalized experience, the CMO Council reported that more than half of consumers will end their loyalties to retailers who do not give tailored, relevant offers. Consumers are also willing to pay more when retailers deliver. According to a RightNow Customer Impact Report, 86% of consumers will pay up to 25% more for a better customer experience.

Driving this level of personalization requires data – and lots of it. Retailers must understand who their customers and prospects are beyond just name and email address. What do they like and dislike? What channels do they prefer to use? What have they recently purchased, added to a shopping cart, or browsed for online? How old are they? Are they married, have children, rent or own their home?

Unfortunately, 80% of marketers are failing to personalize their marketing efforts, according to a study by VentureBeat. Econsultancy found that only 19% percent use personalization in their marketing, even though 74% of marketers state they know it improves customer engagement. While collecting and analyzing this much data may seem like an overwhelming task, retailers who don’t take the time to gather multiple points of consumer information will quickly fall behind. Consumers will instead purchase from the competitors who do know them at this level – even if the price is higher.

So what types of data should you be collecting and how can you use it to drive a more personalized experience?

Begin with Your First-Party Data

Retailers are already gathering data from consumers. A report by Signal and Econsultancy revealed that 81% of marketers exhibiting strong ROI are making good use of their first-party data. This includes information such as purchase history, name and address, phone number, or other similar types of information that are collected as a direct result of a retailer’s interactions with a customer or prospect.

First-party data can be collected from a variety of sources. In a study by eMarketer, senior marketers stated the following top three sources: websites (70%), Point-of-Sales (POS)/CRM systems (63%), and email (61%).

first party data

Making sense of this data can be somewhat puzzling if it isn’t integrated into a single database. Having bits of information stored in a billing system and other pieces of information in a contact management system will be of no use unless this data comes together to form a holistic view of who your customers are. Imagine each piece of data as a puzzle piece and when each new piece is fit together, the complete picture of the consumer begins to make sense.

Third-Party Data

Third-party data is data purchased from other providers. This may be email addresses, phone numbers, demographic enhancements, lifestyle information, real-time behavioral data and other types of data that a third-party vendor compiles from multiple sources. Third-party data allows marketers to “complete the puzzle” and fill in the missing pieces of information to know consumers at a much deeper level.

While third-party data has been around for some time, the breadth and depth of today’s data far surpasses the days of simply acquiring a stagnant list from a broker. When third-party data was discussed in the past, there has always been much controversy about the accuracy and freshness of the data source. True, there are still plenty of list brokers who do not take measures to maintain a high quality source of data. However, data today can now be collected on the fly, cleaned in real-time, and delivered to a marketer on a daily basis. When searching for a third-party provider, be sure they have a solid reputation and ask questions. For example: How do they collect their data? What measures are used to maintain data quality? How often is it refreshed?

Apply Data Analytics

Now that you have collected the data, it’s time to put it to work. Marketers must have a single version of the truth to create messages and offers that will resonate with their target audience. In a recent study by MyBuy’s 2015 Personalization Consumer Survey, consumers purchase more from brands who:

  • 53% – Suggest products based on browsing or buying behavior
  • 49% – Personalize online ads that promote offers and products
  • 48% – Send personalized emails based on past browsing and buying behavior
  • 48% – Personalize the shopping experience across all channels

Delivering this level of personalization requires that consumer data is connected at a very granular level. Apply analytics to create customer profiles and segmentation, and use solutions to update profiles in real-time. Collecting and analyzing data is the foundation of good personalization, but your customer data is constantly changing and must be maintained and updated frequently to ensure relevant customer connections.

Data can fuel great customer connections for retailers. It is the key to delivering the personalized experiences your customers are demanding, which in turn, will drive a huge competitive advantage.

To learn how to implement these data-driven strategies for personalized marketing campaigns, download this free ebook.

Larisa Bedgood
As Director of Marketing for DataMentors, I have a deep understanding of today's data-driven marketing environment, including key components such as Data Quality, Business Intelligence, and Data-as-a-Service (DaaS). I manage and coordinate all marketing functions, including lead generation goals, event and project management, and corporate communications.


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