Data

Four ways data collaboration improves marketing performance

Four ways data collaboration improves marketing performance
Four ways data collaboration improves marketing performance
October 14, 2020
4
by
Richard Lloyd

Data collaboration enables marketers to generate insights and power data activation across first, second and third-party data sources. This collaboration can occur both internally, across business divisions, and externally with trusted strategic partners. 

As we covered in a previous InfoSum blog, a decentralised marketing infrastructure means that data collaboration no longer has to require data sharing and the benefits that decentralisation brings you. Now let’s examine four ways data collaboration can improve the performance of your digital marketing campaigns.

1️⃣ Onboarding data through collaboration

Rather than the current approach, which could be more closely described as data submission than onboarding, data collaboration unlocks a new way to work with identity vendors. 

Traditional data onboarding solutions have required you to upload your customer data into the vendor’s own environment where your data is processed against the data which they hold and then tied to their (interoperable) third-party ID, which only they control. In doing so, you have ceded control of your data to the vendor. This carries associated risks.

Through a decentralised collaborative approach, you are able to match your customer data to the identity vendor's identity graph without that data being merged or pooled with any other data sets. You can then build a segment of your audience that you wish to target and activate against the identity vendor’s various online identifiers. 

This approach not only means you no longer have to share your customers’ personal data with a third-party, but it also enables you to go-to-market faster, as your compliance programme is likely to be much faster. There is also no lengthy matching process within the identity vendor’s environment. 

2️⃣ Enriched customer insights

One of the possible downsides to first-party data may be its scale. It can take time to collect significant amounts of first-party data, the data collected also only gives you a single view of your customers - their interactions with you. 

It has historically been the role of third-party data to plug the gaps in data knowledge and provide an enriched understanding of customers. However, these traditional approaches have required that you either pass your first-party data to a third-party who would enrich it using their insights or that they would share their data with you. Either way, there were huge sums of data being transferred directly between companies. 

A decentralised approach to data collaboration enables data enrichment to take place, without the movement of personal data. Instead of appending new attributes to your first-party data, you are able to match your customers to the third-party data providers audience and analyse the complete picture virtually, using both your data attributes and the data providers. 

This collaborative approach removes the need to share data and delivers both privacy and security benefits, as well as enabling you to unlock insights faster than ever, as there are no delays caused by data transfer and transformation.

3️⃣ Brand to media owner activation

With the downfall of traditional connectivity technologies based upon third-party IDs that are being deprecated by changes to browser technology, brands and media owners have to explore direct collaboration as the way to deliver high performing marketing campaigns. 

Data collaboration enables brands to directly match their customer data to a media owner’s authenticated audience. This empowers brands to create custom audiences, based on both their own knowledge and the knowledge the media owner holds. This insight can power various marketing strategies, including people-based marketing and lookalike modelling. 

This direct matching of a brand’s customers to a media owner’s audience is can deliver greater results for all parties involved. And because InfoSum’s approach is decentralised, it doesn’t require data to be shared between the two parties, so this is all achieved while ensuring the privacy of each company’s customers is protected, as is the commercial value of their data. 

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4️⃣ Accurate marketing measurement

Delivering accurate measurement of the effectiveness of digital marketing campaigns has been the holy grail for marketers for the past decade. Current approaches that rely on last-click-attribution, and similar, do not account for the multi-touch approach of marketing campaigns. 

Through data collaboration, specifically a decentralised approach such as that offered by InfoSum, it is possible to conduct analysis across the various first-party data sources required to paint a full measurement picture. This can include but is not limited to, the brand’s new customer data and the various ad exposure logs across the various marketing channels utilised, retailer transaction data, loyalty card information, location/footfall data from telcos and much more. 

It is then possible to analyse where new customers were exposed to marketing campaigns and build an attribution model that ensures ROI can be accurately determined. 

The future of data-driven marketing relies on collaboration

As data-driven marketing continues to demonstrate tremendous growth, it will be through data collaboration that we see this digital advertising growth accelerate. However, data collaboration shouldn’t come at the expense of your customers’ privacy, or the commercial value of your data. This is why a decentralised approach, that forever removes the need to share customer data with other companies, is truly the future of the marketing world. 

Next time, we’ll examine the role a data clean room plays in providing a safe space to collaborate. Register now to find out first, when that article is published.