• For Buyers
    • Retail News
    • Products & Suppliers
    • Ecommerce
    • Marketing & Management
    • Trade Show News
  • For Suppliers
    • Supplier News
    • Marketing & Management
    • Importing
    • Manufacturers
    • Warehousing
    • Finance
    • Show Exhibiting
  • Wholesale 101
  • Trade Show Calendar
  • Wholesale Products
  • New Suppliers
Facebook Twitter Instagram
Thursday, March 23
  • Subscribe
  • Submit Content
  • About Us
    • Contact Us
  • Advertise
    • Display Advertising
    • Email Marketing Campaigns
    • Newsletter Advertising
    • Sponsored Content
    • Lead Generation Services
  • Top Product Sources
Facebook Twitter Instagram
WholesaleCentral.com Blog
  • For Buyers
    • Retail News
    • Products & Suppliers
    • Ecommerce
    • Marketing & Management
    • Trade Show News
  • For Suppliers
    • Supplier News
    • Marketing & Management
    • Importing
    • Manufacturers
    • Warehousing
    • Finance
    • Show Exhibiting
  • Wholesale 101
  • Trade Show Calendar
  • Wholesale Products
  • New Suppliers
WholesaleCentral.com Blog
Home»For Buyers»Ecommerce»Better Personalized Product Recommendations with Analytics
Ecommerce

Better Personalized Product Recommendations with Analytics

Krystina MorganBy Krystina MorganNovember 22, 20224 Mins Read
Facebook Twitter Email
pressing a button for recommendation
Share
Facebook Twitter Email
  • What is Graph Analytics?
  • Give Shoppers What They Want: Personalization
  • Creating Personalized Product Recommendations Both Online & In-Store

Inflation is causing an uncertainty with consumer spending this holiday season, and retail businesses are struggling to extract value and insights from their data to increase sales and enhance the shopper experience. With 83 percent of customers saying personalization would make them more loyal to brands, this is a crucial factor for indie retailers to utilize to ensure positive holiday sale outcomes. 

“Retail is all about the customer experience and customers are all about personalization. Retail was already a demand-driven industry, but now it is on steroids,” Deena Lawrence, Director of Retail and CPG Industry Solutions at TigerGraph, said. “Consumers have the power to shop anywhere, anytime, and on any device. In some sub-sectors, the products are often the same, so retail must figure out how to differentiate and compete.” 

Graph Analytics Can Help Increase Personalization

Product recommendations are a critical part of retail that often gets overlooked with ecommerce shopping since there are no sales associates able to make this interaction in person. Graph analytics is equipping brands with contextuality and relevant product and personalization recommendations to help enhance the customer experience. 


What is Graph Analytics?

Graph analytics refers specifically to the process of analyzing data in a graph format using data points as nodes and relationships as edges. According to Lawrence, a graph database is fundamentally different from a traditional relational database in how it stores data. Rather than rows, columns, and tables, graph databases are natively built as a network of relationships. 

For example, graph databases are widely used by social media platforms. The data points are people, and the relationships are ‘friends’ or ‘colleagues.’ Using this simple model, Facebook and LinkedIn build very accurate representations of social networks and analyze the data to promote further links, benefits, and personalization. 

“Omni-channel marketing, personalization, and loyalty are ideal use cases for TigerGraph because they are relationship based. 

  • How is the customer related to the product? 
  • Why are customers churning from memberships, subscriptions, and loyalty programs? 
  • What changes in the customer journey would lead to more effective conversion? 

While not all questions are graph questions, the benefits are immense, and it is important to point out that graph technology shows context in data relationships,” Lawrence said. 

back to top


Give Shoppers What They Want: Personalization

Customers are unique, varied, and complex, which can be difficult for businesses to understand, especially at scale. With graph analytics, retailers can convert that weakness into a strength and deliver experiences that are relevant and meaningful. 

“Personalized recommendations boost sales and help retailers build a deeper relationship with their customers by giving them a sense of being understood through engagement, products, and services,” Lawrence said. “Consumer behavior changes fast, and retailers need to be able to understand and respond in real-time to the demand signals that consumers are driving, and it is hard.”

Retailers who can connect with shoppers on this level are connecting at a human and practical level, and that is what consumers want. They want to be seen, understood, and offered something that they need or want and to be served in a way that works for them. 

back to top


Creating Personalized Product Recommendations Both Online & In-Store

While there is still a lot of focus on online and digital channels, Lawrence says retail is a multi-channel operation and the majority of sales are done in stores. One of the most essential exercises for retail is to make sure that the experiences are seamless, irrespective of channel. Graph analytics helps to connect customer data across these different channels. 

With a deeper understanding of shoppers, retailers can choose how to serve them, both in-store and through digital channels. Whether multiple and flexible fulfillment options, or perhaps a journey that started online but turned into an in store, personalized event, or experience based on knowing the customer, the possibilities are endless. 

“The reality is that retail is a demand-driven industry, and consumers are the drivers, so for the foreseeable future, retail must find innovative ways to personalize and differentiate while meeting business goals. Graph databases can perform deep analysis and deliver results in milliseconds,” Lawrence said.

back to top


Related articles:

  • 5 Tips to Boost Ecommerce Conversions
  • 5 Behavioral Science Tips to Boost Ecommerce Conversions
  • How to Optimize Ecommerce Recommendations
analytics personalization
Share. Facebook Twitter Email
Previous ArticleImprove Your Supply Chain With an Effective Data Strategy
Next Article 7 Top Booth Designs to Get the Most Exposure

Related Posts

Best Video Marketing Tips for Retailers

January 19, 2023

5 Ecommerce Tips to Enhance Customer Support

January 17, 2023

Amazon to Increase Selling Fees in 2023

December 19, 2022
Sign Up for Buyer Updates
WholesaleCentral.com

Join the Buyer's Network

Get news & updates only for retailers.

Latest Posts

Amazon Return Pallets For Sale: How to Profit

March 20, 2023

2023 Wholesale Apparel Trends

March 14, 2023

Top Wholesale Easter Products

February 27, 2023

The Future of Sustainable Manufacturing is a Hybrid Approach

February 23, 2023

Make Money with Foreign-Trade Zones

February 22, 2023

Overstock Liquidations

January 25, 2023
how-to
Wholesale 101 for Buyers

Amazon Return Pallets For Sale: How to Profit

March 20, 202311 Mins Read

A big trend among some online sellers is buying Amazon return pallets and overstock and…

Product News

Overstock Liquidations

January 25, 20236 Mins Read

Overstock inventory refers to the excess goods or merchandise that a retailer has on hand…

Retail News

5 Essential Tax Season Preparation Tips

January 24, 202310 Mins Read

Are you ready for tax season? April 18 is approaching quickly, and many day-to-day decisions…

Wholesale 101 for Buyers

How to Create a Google Business Profile

January 18, 20236 Mins Read

Looking for new ways to get your brand noticed? Creating a Google Business Profile can…

  • About Us
  • Subscribe
  • Contact Us
  • Advertise
  • Find Wholesale Sources
WholesaleCentral.com

Join the Buyer's Network

Get news & updates only for retailers.

Follow Us:

Copyright © 2023. Sumner Communications, Inc..

Type above and press Enter to search. Press Esc to cancel.