Whether you’re in the strategy or execution phase of your advertising campaign, discerning the differences between the data that your media and data providers are using can be difficult, if not downright impossible. With so many claims out there about “the best data” and ability to reach your audience “at the right place – at the right time – with the right message”, how can you be sure that the data you’re using to target customers is fresh, clean, and, most importantly, effective? Often times you can’t — until the end of a campaign after your investment has already been spent. By that point, it’s too late, and the business opportunity to capitalize is lost. We’ve compiled ten crucial questions that you should ask any data provider before running a campaign. It will ensure you’re getting the target audience you paid for and could even save your campaign.

1. What is unique about your data, and where is it sourced from?

Why it’s important:

It’s the data provider’s job to convince you that their data is superior, but by understanding how the data is sourced, you’ll be able to see past the pitch and get to the heart of what you are actually buying. Is their data sourced internally (first-party), and, if so, how? Don’t be afraid to challenge the provider and don’t let them rush through this question. You shouldn’t buy any data if you don’t fully understand how it is sourced.

2. What is your reach/targetable scale?

Why it’s important:

Your data provider may have first-party data, but if they don’t have data on a significant number of users, it may be hard to reach an audience at the scale you are looking to achieve. Don’t be fooled by large numbers of data storage terabytes (TB), as it doesn’t speak to the actual audience. Find out how many real people they can actually reach with an advertisement.

3. What percentage of your data is created from a look-a-like model, and can you target solely first-party data separately from look-a-likes?

Why it’s important:

Some data providers can have strong first-party data signals but relatively small scale. In order to artificially inflate their scale, they will use “data science” and look-a-like modeling in order to scale up to a larger reach and to make their offering more appealing. If a data-provider is doing this, you should be fully aware and understand what percentage of the segment is first-party and what percentage is look-a-like. You don’t want the “filler”; you want the real deal.

4. Which signal(s) or action(s) cause a particular user to be placed into an audience segment(s)?

Why it’s important:

If a data provider is looking to sell you users that fall into a particular interest segment, it is important to know what factors have led them to place a specific user in that specific segment. Is a user added to an audience segment after a single data signal, or does it take multiple signals before the user is added to the segment? Generally, a higher number of signals in a given time period indicates a stronger level of user intent, though you should ensure that those data signals are both fresh and relevant.

5. Once a user has been placed into an audience segment, how long do they remain there, and what action (or period of time) causes them to be removed, if at all?

Why it’s important:

Consumer desires fluctuate based on their mood, interests, what they want or need to buy, and even the time of day or month in the year. If a user falls into a segment but does not continue to display interest and intent, they should be removed from the audience segment. As time passes with no additional signals, users are less likely to be interested or relevant to that particular segment. You should be looking for a data provider who has a strategy for keeping their audiences up to date with current engaged users, not with old information. Audience segments with old data lead to advertising that is irrelevant and potentially annoying to those users.

6. Can you explain the process behind how you name/label your audience segments, and the data that feeds into them?

Why it’s important:

Often times, data providers attempt to market their audiences with jazzy names like “home improvement enthusiasts” or “handy husbands”. Just because someone read a DIY article or looked at a toolset online once does make them a home improvement enthusiast. Someone who has looked at 5 toolsets in the past 30 days, read multiple reviews, thoroughly researched them, and then purchased a toolset is much more likely to engage with and be influenced by timely home improvement product ads. This important distinction, along with properly labeled audiences, can lead to more effective targeting.

7. Which devices can you activate on, and can you reach the same user across their multiple devices? How do you achieve this?

Why it’s important:

An omnichannel device strategy is paramount in today’s digital world, where nearly everyone uses multiple devices and navigates between them seamlessly as they go about their day. Reaching that same user on all of their devices allows you to have a consistent conversation with them, keeping them engaged throughout their path to purchase. Ensure your data provider has a device graph (or trusted cross-device provider) linking user devices together for a holistic targeting strategy.

8. In which vertical(s) does your data perform best, and why?

Why it’s important:

Going back to question #1, you’ll want to understand exactly how the data is being sourced. If it comes mostly from sources dealing with a single vertical, such as apparel, ask your data provider to explain why their data performs best for apparel campaigns and what specific signals can point back to the apparel shopper journey.

9. For which metric(s) does your data perform best, and why?

Why it’s important:

You should understand where any data provider’s strengths lie in terms of metrics and performance to be sure that their data strategy and recommended audience segments fully align with your business goals before turning on a campaign. If not, you could be wasting your advertising investment reaching users who are not helping to drive your desired campaign outcome. For example, if you’re looking to increase your brand consideration (share of voice), you should be able to understand exactly how your data provider’s data maps to your brand strategy and what measures they are taking to drive towards your goals.

10. Does your data actually drive brand consideration and/or sales, and can you accurately attribute the performance lift directly to your campaign? If so, how?

Why it’s important:

The end goal of advertising is ultimately to drive sales and show a positive return on investment. A data provider should be able to show you the value of their data with concrete examples of campaigns with directly attributable sales.

Download a printable version of this data provider questionnaire, and ask all of your data and media providers these questions when planning your advertising campaigns — what you find may surprise you. 
Bazaarvoice’s fresh, first-party data audience segments are built from multiple shopping intent signals. Get in touch today to discuss how Bazaarvoice can help you reach your audience while they are truly in-market.
  • http://www.ericgfriedman.com/ Eric Friedman

    Great questions – everyone should be asking all parties this in their ecosystem :)