For Marketing, Big Data Has No Value Without ‘Big Measurement’

by   |   October 22, 2012 12:05 am   |   0 Comments

Martin Smith of TruEffect

Martin Smith of TruEffect

If big data doesn’t enable smarter decisions and actions that drive enhanced performance, harnessing it has no value. Big data only has value when it is accompanied by Big Measurement, which is about challenging organizations to use new data insights in ways that make a positive impact on key performance indicators (KPIs).

This is especially true in the marketing function. In the IBM study “From Stretched to Strengthened,” the company said that 56 percent of the 1,734 CMOs interviewed believed they were unprepared for ROI accountability. ROI is the total return on investment and typically covers media and non-working media costs against the revenue and margin contribution of a customer, either based on a single transaction or on the anticipated lifetime value of a customer. Clearly there is a need to understand not just the explosion of data, but what the data means and how to leverage it.

The performance and cost of performance battle in display advertising will be won by applying the right data with the right measurement and implementing a systematic model that rigorously manages both. When the model is right, the payoff can be exponential. It should be noted this can apply to other media as well, including TV, as more data becomes available at increasingly finer detail.

The current media model is essentially passive media placement and highly summarized reporting. Big data and Big Measurement are ushering in a new, more highly interactive buying and trading model powered by the data. As Forrester analyst Joanna O’Connell noted in her “Future of Digital Media Buying,” report: “Marketers must be much more hands-on in the media planning, buying, and optimization process in this world where the old model is in danger of losing relevancy and effectiveness when it comes to performance and audience-based campaigns.”

What does a more hands-on approach involve? The Big Measurement treatise offers eight principles for building a model that delivers an effective ROI on big data investments.

Data Accuracy. This is oxygen to an organization. There is no point on-boarding great big volumes of transactional data if it is not accurate, nor will ever be accurate. In the digital media space, security software now deletes designated (tracking) cookies almost daily, and Apple’s OS X and iOS do not allow them as a standard setting. This has led to significant inaccuracies in media measurement. It is critical for marketers to ask the tough questions (How was the data compiled? Are the assumptions valid? What are the insights?) and not take the numbers at face value.

Hierarchy. How advertising groups organize data is critical. Big data and Big Measurement make it possible for advertisers to break down the different silos across multiple marketing functions and create an enterprise data and measurement resource. The organization and structuring of this data is one of the most critical parts of design and probably the highest influencing factor to having simply an adequate solution versus a robust solution.

It is a major challenge because each marketing constituency places different emphasis on different elements across the disciplines including media, creative, sales promotions, offers, site optimization, site targeting, web media, mobile media, interactive video, email, direct mail, customer acquisition, customer retention, and so on.

Aligning KPIs to measurement. This sounds like a no-brainer, but it is not uncommon to hear moments of silence in meetings when, after seeing 40 slides of data, the question is asked, “Did it impact our KPIs?” Big Measurement is about understanding outcomes, such as if sales increased, if new customers were acquired, and if brand awareness improved.

Coordinated action.  It is one thing to know something, but quite another to do something with what you know. The configuration of many advertising organizations prevents shared knowledge and coordinated action. For example, customer acquisition and retention are often two separate fiefdoms, which often restricts effective data-driven actions.

If you knew that 20 percent of your media is being consumed by existing customers who account for 60 percent or more of your sales, and your advertising is irrelevant to them, wouldn’t you do something about it? Action can only happen when you align the organization which is made possible by the enterprise data and measurement resource mentioned earlier.

Integration.  One of the biggest impediments to successfully implementing a cogent data strategy for many companies is that their data lives in the domains of multiple vendors. This creates a significant barrier to effective measurement and cohesive data management and results in stitching together data, but not integrating it into a Big Measurement plan.

The further distanced marketers are from their data (retained and managed by third parties) the more prone to measurement errors they become. In addition, the further distanced they are from the point of interaction, the less impactful they can be translating insights into timely and relevant actions. These can be as tactical as targeting or more strategic macro such as media optimization, but in any case effective integration of data is critical.

Stewardship. One of the challenges companies face is to develop effective privacy and data security models that are in line with legislation and maintain the equity of the brand. Studies show that while consumers expect advertisers with whom they have a relationship to be relevant, they do not expect this data to be used inappropriately or shared without adequate notice, choice, and consent. It’s not just what is done with data, but who has access to transactional information in the display advertising ecosystem. In a world of growing data and access, this is not merely a nice-to-have, but an imperative as advertisers need to demonstrate leadership in the privacy area, which continues to be a major concern for consumers.

Right-sizing the program. The most effective ways to implement a cogent Big Measurement approach to big data is to orient the systems at their most basic level to advertising. This removes ambiguity from stewardship, simplifies integration, improves the ability to take action, improves accuracy, and eliminates structures not tailored to the specific advertiser dynamics.

Human capital. The skill sets needed for Big Measurement are as much a part of your success as the technology or framework you develop. Quantitative marketers, people who can demonstrate agility around numbers, are ideally suited to this environment.

Big Measurement challenges marketing organizations to align around new opportunities to create a converged measurement environment that drives relevant customer interaction and results in a significant lift in incremental sales.

Martin Smith is senior vice president and general manager, Ad Platform, TruEffect, a targeted Internet marketing consultancy.

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