There's an endless amount of talk about the importance of data for marketing, but not much talk about how to weigh its value against its cost.

In addition to higher prices for data-driven buys, for example, digital advertisers layering on data might be charged for calls to additional ad servers used for more sophisticated tracking. And in the end, it doesn't always balance out.

How do advertisers evaluate and test whether the data is really worth it?

Ad Age chatted with Rita Ku, chief intelligence officer of Rauxa, which bills itself as "the largest woman-owned independent advertising agency in the U.S.," about how she puts location data providers and other data firms to the test, and why even when the data works once, it may not the next time around.

What criteria do you look at when you're evaluating layering on extra information? How do you go about that process of testing for a client?

The first thing that you would have to take into account is what the client is trying to accomplish with the budget that they have. That will set the tone for how you would test. You think about the uniqueness of the data set, or the scale. So, it's not always both because sometimes you use a data set that will give you scale but it won't necessarily have very special types of variables in there unless you're thinking about a very set audience that you're trying to reach.

Can you give me an example?

You might have a very large data set of adults 18-plus, that's a very common type of data set. But then you have partners that have proprietary data. Maybe geo-location is an example of a type of really interesting proprietary data. Nowadays you have partners who can say, "I can get within ten feet of your business, I can identify people who can get within five yards of where you're trying to target." That value proposition is something that you would consider as a way to get to the right place right time of message delivery.

You start to test the effectiveness of that data set against, let's say, another partner who's just delivering against a very general audience requirement. Ultimately, you're looking for a couple of things. You're looking for reach, you're looking for engagement with the brand, and you're looking for results of some sort, whether that is an acquisition or not.

Are there times when you've had clients say, "This isn't really worth it," or, "This is totally worth it" when they've evaluated a proprietary location data set?

I've seen both happen, and it really is very interesting because as the partner evolves their data set or changes their algorithm it completely changes their ability to deliver against the campaign metric, and it also depends on what you're tracking for the campaign.

I've worked with partners over the years who were great in 2015 and then you use them again in 2016 and they're less so, and you're just like, "What happened?"

What sorts of things have you seen them change that have affected the outcome?

That's not always entirely clear to us. It might not be evident in the campaign results they're delivering. Sometimes it's because of evolving technology or methodology, which became evident when we looked at campaign results.

Is it because they're broadening their parameters for how they're measuring or defining metrics?

It definitely happens all the time and it's definitely part of the partner's secret sauce. It might be the way that they calculate something like multi-dwelling units. It's something as simple as that that can shift the way they are counting individuals or IDs. But it's not always clear to us how that is happening on their end because they shift and they tweak all the time.

But it's also the partners that they're working with as well because some of them are intaking data from a couple of different places. The perfect example is probably somebody like Acxiom. Acxiom has access to a ton of data sources and they have their secret sauce and proprietary algorithms. But if one of those sources suddenly changes the way that they're tracking zip codes, it can really impact the way that the data comes in.

With partners constantly growing their offerings, we stay close with them to understand any changes they make, communicate those changes with clients and regularly evaluate how the data is working within our programs for clients to land on the most effective results.

These location data companies, they're all so young and they're trying to chase what they think customers want. Is it just the nature of it being an emerging sector?

It's very possible because I think the value proposition starts to sound very similar across a lot of these partners. I've heard a lot of different methodologies in terms of tracking. Everybody is trying to find the thing that differentiates them, that is going to make them more accurate.

Ultimately the goals and the KPIs are going to be sort of the North Star of how your evaluations go and the metrics you are going to use to make a decision because, it's not always about scale, it's not always about interaction, and sometimes these partners deliver fantastic results on both fronts. Ultimately, you have to keep in mind what you're trying to accomplish and the cost.

If you're adding dollars, then are you maximizing those dollars in terms of what you're delivering for your business?