Oct 05 2022
8 minute read

Why retailers need both customer and product data

To effectively market the right products to the right people, e-commerce retailers need to utilise the right mixture of data. However, a third (32%) of UK retailers still decide what to promote digitally based on a ‘gut feeling.’

It’s clear that retail marketers aren’t taking advantage of all of the essential types of data available to boost their conversions.

This article will take you through the fundamental data categories you need to improve your online retail business.

Click to jump ahead.

  1. What is customer data?
  2. What is product data?
  3. Final Thoughts

What is customer data?

One of the most commonly used data sources is customer (or consumer) data. This data refers to the personal, behavioural, and demographic information about consumers. The purpose of gathering customer data is to improve your customers’ experience, understand their behaviour and buying decisions, and to grow your e-commerce profits by targeting them effectively with relevant items. 

The main use of customer data is consumer segmentation. This is the strategy of separating your customers into different groups based on their needs, demographics, and buying characteristics, in order to create better campaigns.

There are four main types of customer data you should be obtaining.

  1. Identity data

    Identity data is what information databases use to differentiate someone from everyone else, such as a customer’s name, account login, contact information, demographics, and links to their social media profiles.

  2. Descriptive data

    Descriptive data gives a more detailed picture of a customer. It involves details like education level, career, family and marital status, number of children or pets, home or vehicle type, etc.

  3. Behavioural data

    Behavioural data involves all the different interactions with a company or brand that a consumer has had. This could be transactional data like past purchases, time spent viewing a webpage, abandoned carts, returns, how often an email is opened, communication with a sales representative, and so on.

  4. Qualitative data

    Qualitative or attitudinal data is about what motivates your customers. It seeks to find why someone is more likely to purchase one product over another and includes aspects such as opinions, preferences, attitudes, and motivations.

    As this type of data is harder to obtain, brands generally collect qualitative data through direct communication methods such as surveys, feedback reviews, and customer interviews.


The catch to customer data

While customer data remains an essential resource for advertisers, it’s becoming more difficult to get as personal data policies emerge, such as GDPR and Google Chrome’s expected phasing out of third-party cookies.

As Chrome makes up more than 56% of the global web browser market, the pending change will take a huge toll on the ad industry, especially when you consider that 47% of retail marketers admit that their current strategy is fully dependent on third-party cookies.

With continuous global data privacy policies appearing, it’s clear that online retailers cannot rely solely on customer data. That’s why it’s so important to have a mixture of data resources to base your marketing strategy on.

What is product data?

The second fundamental category is product data. Here we’ll discuss two important types: Product Information Management (PIM) data and product performance data.

Product Information Management (PIM) data

Product Information Management (PIM) is the process of organising and maintaining your product information across your selling platforms. It generally includes all product content and digital assets, such as videos, images, product categorisation, personalisation renderings, and more.

PIM data includes (but isn’t limited to):

  • Product identifiers
    This data covers stock keeping units (SKUs), universal product codes (UPCs),  global trade item numbers (GTINs), and article numbers, as well as product titles, names, and other miscellaneous information.


  • Technical specifications
    This involves technical attributes such as size, colour, fabric, material, and other technical aspects. It can also include information about warranties, weight, measurements, and dimensions.


  • Usage information
    This simply describes when, where, and how your product should be used.


  • Sales information
    This encapsulates pricing information, testimonials, and customer reviews, which can then be used during the sales process or promoted on your website. 

As your business expands, so does the sum of product descriptions, labels, prices, and so on. To maintain and enrich your product information data, we recommend looking into a Product Information Management (PIM) system. 

Product performance data

Product performance data is another crucial, yet highly underused, data source. 

This unique type of data helps you understand the performance of each product through metrics such as number of transactions, revenue, and ad spend per SKU. 

Product performance data also enables you to see whether or not a product positively contributes to your margin after factoring in costs from marketing and other areas –  something that’s key for determining your overall profitability.

With these insights, you can determine your best-selling products, your low-performing products, low and out-of-stock items, ​​and more.

Considering that 64% of retailers still don’t know which of their products have the highest/lowest margin, it’s clear that product performance data is a valuable asset. However, many marketers are still unaware how to access this lucrative information. 

That’s where emerging technologies like Product Performance Management (PPM) platforms come into play. A PPM platform gathers your product performance data from across Google Analytics, Google Shopping, Facebook, and custom sources, and combines it with your product catalogue, giving you insight into how your items perform at the individual level.

You can use this insight to filter your catalogue by whatever metric you choose to create highly specific product sets (e.g. bestsellers, low-performers, new arrivals, etc.) based on your goals.

To see a PPM platform in action, take a look at how Gina Tricot used one to improve their return on ad spend (ROAS) by 83%.

Final thoughts

With a market saturated with competition, it’s crucial that retail marketers use all of the data resources available to them. The fundamental categories are customer data, Product Information Management (PIM) data, and product performance data.

To optimise your online retail company’s success, you should use customer data to understand your target market, use PIM data to stay organised and efficient, and use product performance data to make sure you’re purchasing and promoting the best products to your customers. 

If you’re interested in learning other ways to improve your marketing plan, take a look at The Retailer's Guide to Healthier E-commerce Marketing.

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