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How to Evaluate a DSP’s Measurement Capabilities


There are a wide range of demand side platforms in the market. Some have huge profiles or listings on the New York Stock Exchange. Some are favored by certain agencies, while others specialize in particular verticals.

Nearly all of them claim to satisfy marketers’ every measurement need.

There are a variety of options available for marketers to evaluate DSPs, ranging from free to pricey consulting firms. However, these companies can’t always provide intel with the depth and specificity that many marketers need – particularly when it comes to measurement.

Thus, in our experience, the best way for brands to make informed decisions about which software will meet their measurement needs is to ask the right informed questions. Such as:

Can your DSP go beyond the measurement basics such as tracking impressions, clicks and conversions? Does your product track brand lift metrics? If so – how?

There are numerous third parties that conduct surveys on behalf of marketers to gauge the effectiveness of a particular campaign. Some DSPs have built such a capability into their product, which allows for more seamless, real-time data. Others rely on partnerships or plug-ins.

If driving brand metrics such as awareness and purchase intent are important to your brand – or more importantly, are used to drive optimization decisions mid-campaign – it’s important to know if your DSP can accommodate you. On that note….

Does your platform work with preferred partners for measurement? Or is measurement primarily outsourced?

If your DSP mostly works with outside vendors for brand metrics, attribution, etc., you’ll want to know if your preferred partner is already approved for use within the DSP, as well as how involved your company need to be to ensure measurement is set up properly. For instance, if you’re a CPG company that prefers to measure your entire media plan with a specific partner, is your DSP already integrated with that partner? What does that integration look like? Does the DSP offer in-flight optimizations that complement your overall measurement strategy?

What do all these additional partners cost, and who pays for it all?

These four questions all tie together. Most DSPs, if they don’t have certain measurement functionality built into their platforms, will preach interoperability. In other words, they will claim that their platforms work with any outside metrics vendor – and brands can work with whoever they want.

However, every time a DSP connects with a different vendor, that may require a unique, potentially time-consuming technical integration on the back end, which can slow campaigns down.

Plus, every third party involved in an ad buy needs to get paid by someone. Some DSPs will bake these fees into upfront costs, some will absorb them. But in many cases, marketers are expected to cut checks to each different provider as needed.

Lastly, there’s another factor to consider when DSPs bring on multiple outside metrics purveyors to help steer an ad campaign. The more people involved in implementing and stewarding an individual ad buy, the more chances are that human error occurs.

What kind of match rates does a DSP typically see when marketers bring first party data to the table?

The more that marketers focus on being direct-to-consumer brands, the more they want to use their best asset – first-party data – in ad targeting. Many DSPs offer some avenue for data set matching or have partnerships with companies that can help onboard data or facilitate clean room matches. However, the success rate at which brands will be able to find matches for their first-party data will vary by category, so finding out whether a DSP can find enough of a brand’s users is crucial upfront.

Does your DSP enable brands to resolve customer identity across platforms? If so, how much does it rely on cookies to do so?

Brands have long wanted to keep track of whether their ads are reaching the right audiences, and if they are hitting individual customers with relevant messages in a timely but not too frequent manner. Given the proliferation of digital devices, this was already challenging, and it’s even more so given Google’s gradual phasing out of cookies and Apple’s restrictions on targeting.

Yet many DSPs were built during a more cookie-centric era. Of course, these legacy companies often tout that their products have built-in flexibility and compatibility, and are thus “future proof.” The implication is that these “future-proof DSPs” will perform just as effectively regardless of whatever changes arise in the data-targeting universe. However, many of these new products have yet to prove themselves in a post-cookie environment, and it may be a while before they are able to.

Thus it’s imperative to understand whether they are capable of helping brands resolve tracking the same individuals on different (non-cookie-friendly) devices and how they manage to pull that off. Marketers want to be able to make sure they don’t bombard people with the same creative too often while not reaching key groups often enough. Overall, they want to reduce waste as much as possible.

Can your DSP allow brands to both track incrementality, and make strategic buying decisions to prioritize targeting select audiences? Also, how exactly does your product track attribution?

Increasingly, marketers are seeking ways to make budget decisions based on whether additional media spend will deliver “different” audiences. Will adding a particular new CTV service or social platform help reach people the brand is not reaching with its current spend, for example? If we can measure and isolate such audiences, can we act on that information? The better a DSP is at facilitating this level of optimization, the better a CMO can answer questions such as, “was this spending worth it? Or would I have reached these people already with my other media spending?”

Can your DSP accommodate buying via traditional platforms such as linear TV or audio advertising? If so, how deft is your product when it comes to matching up data sets and identifiers across media?

The more that brands want to be able to manage and evaluate all of their media spending in one place, the more they expect their programmatic partners to be able to service all their buying needs.

We’re seeing this come to a head as more brands look to extend their programmatic efforts to CTV and even data-driven linear TV. Not only have these media not traditionally been purchased using the tools and data sets common to the real-time bidding world of programmatic advertising, but the currencies employed by these media need to mesh. For example, not every DSP is able to translate from a web video buy to a CTV buy to a linear TV buy and back. But from a measurement perspective, this is becoming table stakes as cross-media buying becomes the norm. The DSP of the future needs to be able to buy and measure every form of media, and help a brand achieve a holistic view of their efforts.

How can marketers make the most of DSP’s measurement capabilities?

Even if a DSP seems to offer measurement capabilities that match a marketer’s needs, there’s no guarantee they’ll automatically be set up to make data-informed decisions and justify the value of their media spend. To truly prove the effectiveness of advertising efforts, marketers need to how to choose the right KPIs and set up their campaigns to be accurately measured.

That’s the reason behind Viant’s white paper Measurement Tactics for a Cookieless World. In this four-step guide, Viant’s SVP of Platform Automations and Analytics lays out a plan any marketer can undertake – regardless of the coming end of cookies.


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