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Oracle Data Cloud Blog

Why your DMP struggles with match rates (Part II)

This week’s guest blog post is contributed by Jeffrey Lin, Senior Sales Consultant, Oracle Data Cloud.

In our last post, Why your DMP struggles with match rates, we discussed the important role a partner network plays in enabling higher match rates for data ingestion into a data management platform (DMP).

In this post, we look at how that same partner network also helps a DMP deliver more data to downstream partners. 

For DMP operators, media planners, and advertisers, data deliverability is just as important as maximizing your match rates.

Whether you are sending data to downstream media partners like The Trade Desk or Amobee, or to site optimization partners like Maxymiser, the ability for a DMP to effectively deliver data is the key to ensuring your campaigns are executed on schedule and with maximum reach.

To illustrate this, imagine starting off with an audience of 1MM profiles from your CRM, offline file, or transactional file.

If we assigned a monetary value on average of $5 for each profile, the perceived value of your file is $5MM.

Through offline onboarding, we could potentially lose anywhere from 10 to 40 percent of our entire audience, depending on myriad factors.

Considerations such as the amount of customer profile data available in the offline files, the robustness of the onboarding partner, and the scale of the partnership network of the DMP are all reasons for data loss.

Subsequently, we might lose another 20 percent of those audiences to the downstream media partner for reasons we will cover in this post.

In the end, our original $5MM file is now worth about $2MM. A drop of 60 percent results in $3MM in losses because of data interoperability issues.

The question then becomes why does data loss happen when sending our audiences to media partners? There are three reasons for this.

ID swaps

Data travels a long way to appear inside of The Trade Desk, Amobee, MediaMath, or Google.

Each of these respective partners works differently from each other when it comes to data collection, transformation, and categorization.

While that conversation is best saved for a future post, ultimately a DMP’s responsibility is to ensure their DMP ID is translated to the partner’s own IDs.

That is where the process of ID swaps becomes integral in all of this.

Many of these IDs are based on either cookies or MAIDs (Mobile Ad IDs), and no two IDs are alike.

Every media partner, including Amobee and MediaMath, develops their own proprietary IDs and are unable to directly communicate with each other.

Hence, a complex process—that we will simplify—known as ID swaps occurs for these IDs to be properly exchanged.

ID swaps typically take place on a brand’s own website. When a new visitor lands on the website, they are immediately identified with a cookie, which is then mapped to your DMP’s ID.

This ID is exchanged with all of the media partners who coinhabit the same website as the DMP JavaScript tag.

Although this is a simplified view of how the ID swaps happen, it gives you a good idea of the process. We will expand on the concept of ID swaps soon.

For visitors to be targeted in an ad campaign, they must have visited your website at least once to be identified with an ID.

If that user never shows up, then the downstream media partner will not receive the audience to fulfill the campaign.

Remember, the time it takes for a media partner to receive your audience can take weeks or months depending on the DMP and media partner used.

Cookie refresh

While the world is slowly moving to a cookie-less landscape, the venerable cookie still plays a big part in the media ecosystem.

Cookies allow a site to identify whether the user is someone who has previously visited the site or is a new user.

The downside to cookies is that they will expire or users can easily “cleanse” all cookies from their browsers.

Typical cookies might have a shelf life of somewhere between 14 to 30 days, depending on which vendor sets it.

If you depend on your website for ID swaps, you essentially have a 30-day window to identify that site visitor or you’ll lose them to the abyss. They will never reach your downstream partner.

Missing data

The Harvard Business Review states that projects typically spend about 12 percent of their budgets on data-cleansing efforts resulting in a 4 percent cost overrun. If you feel your data cleaning efforts are ongoing, you aren’t alone.

In the media world, everyone has some sort of data quality issue with missing contact info, email address, and identifiers.

While this is a challenge to resolve, know there is currently no way to deliver data if your dataset is bad to begin with.

Improving your match

So how do we, as marketers, mitigate this? The sad truth is there isn’t one silver bullet to solve your match rate issues.

But, outside of the missing data piece, ID swap and cookie refresh can be easily solved with the right DMP architecture in place.

If you are in market for a DMP, consider looking at one with a built-in partner ecosystem where data loss can be mitigated.

With 15MM+ partner websites, the Oracle BlueKai DMP leverages the power of our partners to help conduct ID swaps and to deliver the right IDs to the downstream media partner outside of your own websites.

In fact, our customers enjoy some of the highest data deliverability rates of any DMP in the marketplace today.

If ID swaps happen across millions of sites in real time, then we can effectively solve both the timing and cookie refresh problems we touched upon.

Find out how the Oracle BlueKai DMP can help you reach more people, drive greater revenue, and optimize media spend.

Get our checklist with our top questions to ask your DMP provider.

For more questions about match rates and the DMP, head to The Data Hotline

About Jeffrey Lin

Jeffrey is a marketing and advertising technology veteran whose career spans more than a decade.

As a senior solutions consultant, he believes in helping marketers to get the most out of their technologies.

Stay up to date with all the latest in data-driven news by following @OracleDataCloud on Twitter and Facebook!

Image: Shutterstock

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