Egen Solutions and SpringML have merged to unleash the power of cloud, data, AI, and platforms for organizations. Our combined company is now named Egen.

We are excited to bring together our two companies, joining platform engineering expertise and experience with data, AI, analytics, and cloud capabilities to strengthen the impact and value we deliver for organizations advancing their digital journeys.

You can expect the same high standards from us as we combine forces to bridge technology and human empowerment.

Btn Arrow Btn Arrow
Read the Press Release

How AI Can Enhance Your Product and Customer Experience

Written by

Ashwin Hariharan

Published on

Feb 11, 2021

Reading time

13 min read

  • ML & AI
  • Innovation
  • Retail
  • Launch

A deep dive into implementing AI-based analytics to help transform your product experience and build strong brand loyalty.

American Marketing Association

The world runs primarily on people’s emotions. Their perceptions influence their actions, which largely shapes reality. In this article, we’ll take a dive into a small subset of our world — retail.

You’ve heard the saying — Customer is King. As cliche as it sounds, it is a timeless one. If you’re into the retail business, your customer’s emotions and experience largely determine where and how they spend money   and it’s usually on things that make them feel good. So in theory, if you’re able to influence the experience of your customers, the better it does for your business. The customer’s perception is your reality.

It’s no wonder that in this age of internet, many e-commerce and retail companies pour billions of dollars into understanding the billion dollar question —

How do I make my customers happy?

This is an ageless question with no easy answers. Committing to a brand has become harder than ever. Competition is fierce and customers are faced with the paradox of choice. Retailers are now faced with some hard challenges:

Challenge #1: Inconsistent Channel info

Keeping product catalogue and information consistent and updated across all different channels is a major one. With so many channels to buy from, it is common for product information to get outdated or redundant, and customers can get overwhelmed and confused by redundant or irrelevant information.

Challenge #2: Redundant and Repetitive Processes

A lot of in-store and online operations, labor work, and customer engagement are repetitive in nature and difficult to scale beyond a threshold.

Challenge #3: Lack of market insight

Knowing where the market trends are heading is crucial for any business. This means having a historic view of purchase patterns and the ability to forecast sales in the near future. Do you know what your customers are really looking for?

Challenge #4: Scale

With so much information pouring in, how do you scale up your operations?

Inevitably, retailers are turning towards technology as a means to improve the shopping experience and solve the problems which come with scale. Over the years, various kinds of software for e-commerce have emerged to handle mission critical processes like:

  • Inventory Management
  • Payment Processing
  • Point-of-sale, Invoicing/billing
  • Marketing Management

But now we have another problem — Information Silo.

A data silo is a management system in which one information system or subsystem is incapable of reciprocal operation with others that are, or should be, related. Many software solutions exist that aim to solve problems like inventory management, marketing or sales, but they don’t seem to work together.

There is a real need for omnichannel approaches. Omnichannel involves the integration and orchestration of multiple channels and software retailers would commonly need. It makes life much easier this way, rather than the cumbersome and inefficient process of using single channels in isolation.

Recognizing existing problems and opportunities, we aim to build a standalone PIM (Product Information Management) system that:

  • Focuses on product catalogue management which provides a full variety of features that are simple to use, well-visualized, and utilizes smart search.
  • Has robust infrastructure for data import, transform, integration, and distribution.
  • Is equipped with artificial intelligence & machine learning to automate and streamline manual operations.
  • Is cloud-based, to fulfill the customer’s need to quickly scale and pivot.
Mordor Intelligence

Product Information Management (PIM)

To put it briefly, a PIM is a multichannel marketing software tool that allows real-time tracking for all data contained in a company’s catalogues and inventory by sending it appropriately to all channels and ensuring every channel connects with each other.

Why PIM?

Over the years, e-commerce has witnessed earthquake changes that call for innovative solutions:

Omnichannel information consistency and precision has become life-or-death.

  • 50% of consumers have reported sending a product back because it didn’t match its description
  • 59% of consumers expect a company to have consistent information on every channel
  • When content does change, 60% expect a company’s website(s), emails, and distribution channels to all reflect these changes on the very same day

Smart product content personalization with artificial intelligence has become the game. Play it or lose it.

  • 79% of consumers will only engage with personalized offers
  • Increasing personalization across channels can boost consumer spending by as much as 500%
  • Shoppers who click on personalized recommendations are 70% more likely to make a purchase

Automation and streamlining in product information management can save huge costs.

  • Businesses employing PIM automation improve up to 25%, annually
  • 25 min per SKU per year is spent on manual item data cleaning, which would take only 4 min with automatic synchronization
  • Before the introduction of a PIM system, less than 47% of staff at retailers spend less than 2h per week searching for products. After implementing PIM, this percentage grew to 58%.

Cross-border shopping is booming.

  • > 57% consumers make purchase from other countries
  • 92% consumers prefer to shop in local currency
  • 59% consumers rare or never use English-only websites

Let’s explore further.

Key capabilities of a PIM system

  1. Organize/Centralize: From a company’s ERP, where data files are stored (flat files, excel sheets etc.) including other sources of product information like resources of images and videos, a PIM system collects all such material and channels it in the right directions.

It is responsible for searching elements, managing the translation of descriptions,, classifying categories, correcting errors, editing and updating changes, enriching product descriptions, synchronizing their presence in all areas.

2. Analyze/Optimize: On top of organization, PIM can also provide you with a Gap Analysis and quality report of your data.

3. Connect/Distribute: Through a PIM, members with access to the system can organize and classify products according to the categories and labels desired, and update any associated data, such as prices, product features or images that will appear equally on all platforms linked to the PIM system.

Inconsistencies between physical and online catalogues or between products in the same collection that have different data sheets will be greatly minimized.

Now with this intro, let’s look into the intelligence that drives some of these features.

The role of AI and ML in a Product Information Management System

Machine learning can be used to automate and make many of the manual processes much smarter in a PIM. Here are a few applications:

Application #1: Backend Catalogue Data Processing

We can start by streamlining and automating manual process of importing product data with AI.

Technology behind the scenes:

Python has a robust ecosystem and open source libraries that help with data imports, extraction, and manipulation.

For extracting product information, we can use python-tesseract  an Optical Character Recognition (OCR) tool for python. That is, it will recognize and “read” the text embedded in images.

Python-tesseract is a wrapper for Google’s Tesseract-OCR Engine. It can easily read all image types supported by the Pillow and Leptonica imaging libraries, which mainly includes jpg, png, gif, bmp and tiff etc.

The main functionalities that it supports are:

  • AI to identify raw data, either CSV, EXL, PDF, images, to extract the data piece needed.
  • Auto-populate essential product data (name, title, description, etc.)
  • Automatically standardize data imported to be a uniform format
  • Visualized drag-n-drop/linked graph (or any other methods around visualization), for the user to understand how the data is transformed, and make any changes (e.g. ProductsUp)

Let’s understand with an example:

Application #2: Front-end catalogue management

Here are a few features you could build:

  • AI-powered search function to get rid of complicated hierarchy and categories (text auto-completion, key word associations, etc.)
  • Web-scraping existing competing products before new product launch, providing competitor insights.

Check out How Web Scraping Crawler Lambda Function can be implemented using AWS AI and ML services

Gathering Market Intelligence from the Web Using Cloud-Based AI and ML Techniques | Amazon Web Services
Many organizations face the challenge of gathering market intelligence on new product and platform announcements made by their partners and competitors—and doing so in a timely fashion. Harnessing these insights quickly can help businesses react to specific industry trends and fuel innovative produc…

Application #3: Performance analytics

Predictive modeling of past trends of demand, for marketing and sales purposes. Time-series analysis and forecasting methods are the most commonly used approaches.

Technology behind the scenes:

  1. Statsmodels
  2. ARIMA
  3. Facebook Prophet
  5. XGBoost

Here’s a sample ode for implementing Statsmodels, ARIMA and Facebook Prophet in Python:

Using the sample code, you’ll understand how to implement the following features:

  • Link to inventory management for inventory tracking and real-time product availability (SKUs)
  • ROI strategy recommended by analyzing poor-sold and better-sold products
Fig: Time-series Analysis

Application #4: BI dashboard to show product selling performance

Now coming to the visualizations, “plotly graph_objects” has been used to build the BI dashboard.

Why is Plotly a great exploratory tool for data scientists?

A major advantage of using Plotly is that it encourages us to be as creative as possible with your visualization since any complex plots only use three main concepts: data, layout, and figure objects. As an Engineer, this is probably one of the best things to have as we can build and rebuild graphs in any way we want. Here’s an article that explores this in greater detail.

Check out some examples of the kind of visualizations that you could build:

Hopefully you’ve understood what Product Information Management is all about. But not everything is about information! Establishing a PIM system in your business is the beginning of a larger goal, known as:

Product Experience Management (PXM)

It’s necessary to understand that this is not the same thing as PIM. PIM (Product Information Management) system is the foundation for PXM. Product Information Management software provides all product content and remains a crucial element and enabler of the practice of Product Experience Management, focusing on the content aspect of the product experience.

In other words,

PIM system is WHAT business use to describe products and services, but PXM is HOW you stage an experience. —

5 ways to reinvent your conversion strategy with experience driven commerce

#1: Automated Content Planning and Creation

Machine learning can perform beyond simple content creation; it can enable marketers to better use that material for more impact. For example, ML tools can analyze both competitor strategies and user behavior to determine the best approach to engage with potential customers.

Here’s how you can build a simple content planning and creation algorithm using Amazon Personalize:

amazon-personalize-samples/next_steps/core_use_cases/user_personalization at master · aws-samples/amazon-personalize-samples
Notebooks and examples on how to onboard and use various features of Amazon Personalize - amazon-personalize-samples/next_steps/core_use_cases/user_personalization at master · aws-samples/amazon-pe...

#2: Smarter Product Content Personalization

The value of machine learning lies in the ability to create opportunities from data, and it’s already changing the way marketers manage their campaigns. From producing trillions of dynamic ad variations to formatting them across platforms in milliseconds, machine learning frees up creative staff to focus on creative ideas and strategy.

Dynamic Web

Dive Deeper : How to build it with Amazon AI Service — Amazon Personalize

Amazon Personalize can now create up to 50% better recommendations for fast changing catalogs of new products and fresh content | Amazon Web Services
Amazon Personalize now makes it easier to create personalized recommendations for fast-changing catalogs of books, movies, music, news articles, and more, improving recommendations by up to 50% (measured by click-through rate) with just a few clicks in the AWS console. Without needing to change any …

#3: Conversational Commerce

Conversational commerce or trade is a system of direct communication between a brand or business and its customers, through instant digital messages that are shared on platforms such as WhatsApp, Facebook Messenger, iMessage, Viber or Alexa de Amazon, and that incorporate the ability to make purchases online. — pimnews.orgFor example H&M chatbot gives customers advice by analyzing the preferred choices of their looks. According to this, chatbot picks other matching stuff to describe their personality, favorite style, and so on.

Dive Deeper : How to build it with Amazon AI Service — Amazon Lex

Conversational AI and Chatbots - Amazon Lex - Amazon Web Services
Amazon Lex is a fully managed AI service for building conversational interfaces into any application. Start creating a chatbot, voice assistant, ML-powered IVR, or virtual agent today.

#4: Augmented Reality

There are several emerging technologies which can help enhance a customer experience such as 3D, Augmented Reality (AR), and Virtual Reality (VR). These immersive solutions are like super-powers for your product information. They can be used to create a more rich, realistic, and appealing buying experience. In addition, they increase effectiveness as 3D interactive content drives 94% increase in page views and helps reduce costly returns.

A better customer experience with a higher conversion rate and fewer returns can mean more revenue.

Dive Deeper : How to build it with Amazon AI Service — Amazon Sumerian

Introducing Amazon Sumerian by Tutorials!
Create unique 3D, AR and VR experiences with our new book, Amazon Sumerian by Tutorials!

Market Growth of PIM

MarketsandMarkets estimates the global PIM market size is expected to grow from USD 9.0 billion in 2020 to USD 16.0 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 12.2% the forecast period. The major factors driving the growth of the PIM industry include rising demand for PIM solution from flourishing eCommerce industry and increasing need to offering enhanced customer services.


Product Experience Management is crucial to customer experience. Every interaction you have with your customers is an opportunity to create something truly remarkable. The product information you provide is an integral part of the customer journey. The quality of your product data influences the trust in your brand, your products, and ultimately the customer’s buying decision.

What’s the expected business impact?

If you’re interested in integrating AI and ML in your existing business solutions, give a shout to us on social media or reach out to us.

References and Sources:

ML Powered Product Categorization for smart shopping options

An End-to-End Project on Time Series Analysis and Forecasting with Python
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics…
The New Beginnings of AI-Powered Web Data Gathering Solutions
Are you approaching data gathering on a large scale in a traditional manner? If so, expect to invest a lot of time and effort into proxy…
Optimizing Product Content for Voice Search | Magnitude Agility PIM
4 main strategies for product content managers to capitalize on the opportunities of voice search to Prepare PIM for Voice Search & Optimize product content
5 Benefits of Automation and How PIM Solutions Can Help - Innovit
Ah yes, the benefits of automation…having technology do things for you so you don’t have to. This is particularly true of automating product information management (PIM). As business owners, manufacturers, and digital marketers, you need your business to run as efficiently as possible and incorporat…
Product Information Management
Product Information Management is the latest topic that companies across the world are deliberating upon. As companies sell online, they are confronted with the fact that not all information necessary to sell their products is available. Where marketing, sales and finance have been core processes of…
50 Stats That Prove The Value Of Customer Experience
Customer experience is incredibly valuable. Without a customer focus, companies simply won’t be able to survive. These 50 statistics prove the value of customer experience and show why all companies need to get on board.

Liked it? Share it with your network

You might also like

All Insights