Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
    data analytics for trademark registration
    Optimizing Trademark Registration with Data Analytics
    6 Min Read
    data analytics for finding zip codes
    Unlocking Zip Code Insights with Data Analytics
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: How to Personalize the Retail Experience with Data
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Modeling > How to Personalize the Retail Experience with Data
ModelingSocial Data

How to Personalize the Retail Experience with Data

Lbedgood
Lbedgood
7 Min Read
SHARE
personalize retail

How to Personalize the Retail Experience with Data

Leading retailers have made great strides in becoming omni-channel, multi-channel marketing experts.

personalize retail

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%).

Beacon 3

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.

ebook shorter

Tags: 
retail, personalization
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

crypto marketing
How a Crypto Marketing Agency Can Use AI to Create Powerful Native Advertising Strategies
Blockchain Exclusive Marketing
data driven insights
How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
Analytics Big Data Exclusive
image fx (37)
Boosting SMS Marketing Efficiency with AI Automation
Exclusive
pexels pavel danilyuk 8112119
Data Analytics Is Revolutionizing Medical Credentialing
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Image
Big DataBusiness IntelligenceData MiningPredictive AnalyticsSentiment AnalyticsSocial DataText AnalyticsUnstructured Data

That’s Sick! Text Mining and Words with Multiple Definitions

4 Min Read

ACM Data Mining Talk: Representing Solutions with PMML

2 Min Read
Image
Best PracticesBig DataData ManagementPrivacySocial Data

When Privacy is Good Business

9 Min Read

Creating Beautiful Maps with R

3 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?