Whilst first-party data can provide rich and meaningful insights on your customers and can feed into machine learning, it often lacks breadth, especially if your business isn’t able to collect, store and manage valuable high quality first-party data efficiently.

This is where third-party data comes in.

Third-party data refers to data that is collected by organisations outside of your company and can be used to gain valuable insights into your target audience, industry, or market.

In this blog post, we’ll explore the reasons why third-party data is so important and how it can benefit businesses of all sizes.

#1 Close the gaps in your data

A lot of organisations are collecting their own first-party data to help derive actionable insights and gain a greater understanding of their customers to then guide decision making.

This could be:

• Website data
• Social data
• Marketing data
• Operations data
• Sales data

Whilst this first-party data can be very high value, unless you have a large quantity of it, it often lacks validity and is not enough to base high-level decisions on. This impacts the quality and reliability of your analysis.

In this scenario, third-party data can be used to close the gaps to enhance the value of your insights and findings. Put simply, third-party data cannot match an organisation’s first-party data, however, it can help you build on to the insights you already have. First-party data lays the foundations, third-party data heightens it and allows you to broaden your data ecosystem.

#2 Greater context into customer behaviour

Even if your business is a well-oiled machine when it comes to collecting first-party data, this is often useless if you don’t understand the macro-economic factors driving consumer behaviour.

This could include:

• Geographical trends
• Demographic changes
• Environmental changes
• Political news
• Market share/size information

By utilising third-party data, you can obtain insights that will help you to understand current behaviour and predict future behaviour, so you can calculate any impact on business operations, and gain greater insights into supply and demand shifts.

#3 Understanding your target audience

Third-party data can help you better understand your target audience and their behaviours, interests, and preferences. This information can be used to create more targeted marketing campaigns and to develop more effective customer engagement strategies. For example, if you’re selling athletic clothing, you might use third-party data to learn more about your customers’ exercise habits, which can help you create content and promotions that resonate with them.

#4 Strengthen Indirect Sales Insights

Third-party data is also pivotal if your business operates through indirect sales channels, as it enables you to gain insights into your sales activity through each third-party retailer. Without it, you only have a partial understanding of your sales performance.

For example, if you were a company selling computers direct to the consumer, but also indirectly through a retailer, you would have access to certain information, such as no. of units you were providing to the retailer, product price point and location where the units are sold. However, you’d be missing a range of insights such as how the retailers discount & marketing schemes impact sales, whether the user is purchasing online or in person, or if certain areas of the world sell better than others.

This is where you can really benefit from utilising third-party data to gain more granularity into your indirect sales performance.

#5 Improving marketing and advertising efforts

Third-party data can also be used to improve your marketing and advertising efforts by providing a more complete picture of your target audience. As a result, you’ll be able to offer a deeper level of personalisation to help your ads resonate more with your target audience.

For example, you can use third-party data to create more effective targeting strategies for your digital ads, such as targeting based on demographics, interests, or purchase history.

This information can also be used to improve your email marketing campaigns by personalising your messages and making them more relevant to your subscribers.

#6 Making informed business decisions

Ultimately, third-party data can provide you with the valuable insights into your industry and market that can be used to make informed business decisions. It allows you assess the competitive landscape, identify market trends, determine the best target audience for your product and predict future customer behaviour. Combined with your first-party data, this information can provide you with a complete picture that will then guide your business in terms of pricing, distribution, product positioning and much more.

In conclusion, third-party data is a valuable tool that can help businesses to close the gaps in their data, gain greater context into customer behaviour, build a better understanding of their target audience, strengthen indirect sales insights, improve their marketing and advertising efforts, and ultimately make informed business decisions. Whether you’re a small business just starting out or a large corporation looking to stay ahead of the competition, incorporating third-party data into your data strategy is essential for success.

How Ipsos Jarmany can help you

Managing your third-party data can be a minefield, especially in a privacy conscious world with increasing regulations around data protection and misuse. It can also be a struggle to integrate this third-party data with your existing data, and using this to build and feed machine learning models to gain enhanced insights. Additionally, this type of data management requires a specialised skillset, which is often very timely and expensive to build internally. As a result, leaning on a specialist agency, who have expertise in storing, managing and transforming data in order to gain actionable insights is often the favoured approach.

Get in contact with us today if you’d like to explore how we can help you manage your data, use techniques such as web scraping to obtain more insights, and then build machine learning models to help you drive business growth.