Why PLM consultants are questioning new tools and asking about cloud exit strategy?

Zachary Rosenberg President at MBMG

There is incessant talk and articles written about data analytics. The future has arrived, we are told sternly, and marketers who haven’t gotten on board are missing critical insights that will take their businesses to the next level. We’d like to add to that conversation, but our angle is a little different and might be considered something of a reality check.

Performance analytics and data-driven media decision-making are necessary capabilities of the modern media agency, and while we’ve seen some intelligent and responsible applications of data within our industry, we’ve also seen some absolute nonsense paraded about. We hope that our experiences will help you see that while some of these offerings sound extremely sophisticated, you shouldn’t be too intimidated to ask questions about methodology, or too trusting to accept everything you hear at face value.

The benefits of utilizing a client’s own 1st party data and drawing on the seemingly endless resources of 3rd party providers may sound like relatively straightforward uses of current technology. However, time and time again, we’ve noticed some serious flaws in many of the latest agency and vendor offerings.

When we peek under the hood, we see that many of them:

· Operate under a guiding principle that more data is simply better.

· Provide efficiency recommendations based solely on crunching whatever numbers are available rather than carefully considering which data sets are appropriate.

· Focus exclusively on the consumer audience while ignoring the content audiences.

· Are so complicated that users may interpret the data incorrectly.

One must be able to understand the underlying merits and limitations of the originating data sources that feed the tools you’re reading about in the industry press. The land rush to deliver the latest and greatest cutting-edge solution has resulted in marketers having to place their trust in black box products, some with gorgeous Graphical User Interfaces (GUIs), but with data gaps sizable enough to call into question any findings.

The two most typical issues we come across are both data-related. In some cases, tools are built on a fixed set of household-based information. It’s not that household data is incorrect, it just may not accurately reflect the attitudes, choices and behaviors of the intended prospect, potentially skewing media decisions to the wrong person in the household. In other cases, we’ve seen an over-reliance on data that is readily available and the omission of highly relevant information necessary to make comprehensive evaluations.

We don’t go into these evaluations lightly or with the sole intent of poking as many holes in products as possible. In fact, we usually offer suggestions for improvement, and in some cases, have tried to correct interpretations with even more favorable readings of the data. Companies like Nielsen, Ipsos and SMRB have been receptive to our suggestions in the past.

It is, however, somewhat disheartening and alarming that some companies are more interested in fast-tracking sales or making waves in the press than in making a better product.

Agencies must lead clients by taking a more thoughtful and meaningful approach to harnessing the power of big data. InsightPLUS at MBMG connects 1st party and 3rd party resources using world-class data partners such as Acxiom, Claritas and Experian and sources accredited by the Media Rating Council (MRC) to ensure the highest standards of quality control and transparency. These unimpeachable guardrails help us deliver more accurate target insights and media recommendations.

There are four fundamental concepts that we take to heart:

1. Household data doesn’t necessarily best reflect the preferences and behaviors of actual consumers, so we also apply person-level characteristics and behaviors to help fine tune our targeting analysis.

2. We identify media placement recommendations that will appropriately serve the creative and amplify the messaging— on-strategy vs. off-strategy, a foundational tenet of communications planning that is lost in data-only solutions.

3. Thorough efficiency evaluations should be based on both audience compatibility as well as target reach. This is especially true for programmatic television solutions which are actually “fauxgrammatic” because truly addressable 1-to-1 messaging is still extremely limited.

4. It’s important to be cautious when using big-data insights. The math may be correct, but the insights can only be as good as the inputs used and may not be actionable due to data instability. Being aware of, understanding and navigating through these limitations separates a true media expert from the garden-variety media planner.

So, if you’ve ever scratched your head over big-data recommendations that just don’t seem reasonable, you’re not alone. We’ve seen it often enough to give us pause. Agencies need to dig deep and call out ill-conceived design and uninformed uses of data. Marketers should learn more about the tools being applied to their businesses and shouldn’t fall so easily under the spell of “what’s new” in order to claim forefront status. A dose of reality will go a long way to ensure you’re managing data and making the best decisions for your clients and their business.

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