Five Obstacles to Digital Measurement, And What To Do About Them
In the age of Big Data, the measurability of digital interactions takes front stage. We are lured by the promise that all touch-points are measurable and believe that measuring and improving program impact should be straightforward.
Yet, instead of being empowered by digital data, many marketers we’ve spoken to say they are overwhelmed by it.
In our experience, there are four obstacles which, once addressed, will go a long way toward unleashing the measurement insight available to you.
Here they are:
- Inadequate education – Understanding the terminology surrounding digital data is like learning a foreign language. Unless we understand these terms and how to use them, it will be difficult to gain control of our digital investments. To test your knowledge, ask yourself how many of these questions do you know the answer to, and see answers at the end of the article.
- What does KPI stand for?
- Knowledge, Perception, Intelligence
- Knowledge Platform Indicator
- Key Performance Indicator
- Key Performance Initiative
- True or False: a unique user is the same as a person?
- What is an A/B test? __________
- What is a DMP and why would you need one? ________
- What does KPI stand for?
- Ill-defined cross-channel performance objectives & KPIs. Our consultants have been in numerous meetings where someone will say something like “We achieved X unique users to our website last month.” What’s often missing, however, is a sense of whether that result is good or bad, and how it ties to expectations and an overall business impact measure. In other words, you’re missing clear performance objectives (defined at both a channel and cross-channel level), tied to discrete KPIs and derived from relevant benchmarks.
- Fragmented reporting. A marketing or communications team typically works with a number of different partners (agencies, publishers, marketing services and research companies), each of which supplies different reports, at different time intervals. The problem is compounded when different brand team members take responsibility for different tactics and each collect their own reports in isolation, thus obscuring the bigger picture. And, perhaps most importantly, a synthesis of the digital data that is collected rarely finds its way into broader brand scorecards, which command senior management’s attention. Too often, the net result is that digital data remains siloed and not meaningfully integrated into brand decision-making.
- Limited action. Too often digital measurement is focused on justifying past plans, to prove their worth. When this is the prevailing mind-set, pharmaceutical companies focus on reporting over optimization. As a result, they miss large opportunities to boost performance through experiments that drive continuous improvement. Pharma will not soon be able to imitate Amazon, which conducts hundreds of experiments a year to boost sales, but that doesn’t mean that optimization can’t play an important role.
- Unclear ownership of digital measurement as a competence. Many companies have groups that take accountability for developing sales excellence or brand planning excellence. But, where does digital measurement sit as a competence? Is it a brand responsibility? Market research? Sales operations? The Digital COE? IT? Some combination thereof? One of the reasons the first four obstacles exist is because responsibility for competence and infrastructure development is not well defined. The truth is that digital measurement touches all of these areas, so role definition is paramount.
To address these obstacles at your company, consider these five actions.
- Define digital measurement competence accountability. If you are a senior leader, you may be able to take direct action to address this issue, or appoint someone to do so. What’s needed is clear accountability for digital measurement as a competence. This accountability can be assigned at the enterprise level, for a franchise or for a brand. But someone should be charged with ensuring there is a consistent approach to digital measurement, including competence education, benchmarks, goal-setting reporting standards, measurement tools and infrastructure. Remember, it’s not enough to rely on vendor partners alone, or you’ll end up with the fragmented approach described above.
- Engage in education. Education is a foundational step that will pay back in spades. Ideally your company will finance the education as part of a larger effort to boost digital measurement competence. That effort would ideally begin with a self-assessment to help marketers understand where they stand. But, if no such program exists, marketers can take measurement learning into their own hands. There are several resources available, ranging from free online resources to paid consulting, that provide very thorough primers to help you climb the learning curve quickly, regardless of your current level. (Feel free to contact me for suggestions.)
- Develop a cross-channel measurement plan. Measurement planning is a critical step that is too often missed or handled incompletely. A high quality measurement plan will clearly define the overall objectives of the multi-channel campaign overall and each tactic, and the KPIs that allow us to gauge success. It will also define the sources of data, the reporting to be generated and the plans for optimization. Many companies have measurement plans for individual channels but the most valuable plans are those that look at performance against aggregate KPIs that cross channels. For instance: what is our reach, engagement or conversion against a given segment across channels versus a single channel alone? To generate a cross-channel measurement plan, it’s important to bring together all the different stakeholders so all of the different pieces are represented.
- Standardize, consolidate and automate reporting. This is where the rubber hits the road and we learn how our programs are reporting. The default state is that each data provider develops its own reports, in its own formats, and distributes them on its own schedule. This creates an overwhelming amount of information for brand leaders and prevents answering basic business questions about cross channel performance.
Overcoming this issue requires standardizing reports so there is consistency in how the reports are created. Ideally, brands across the enterprise should have common definitions around KPIs and standard report views for each channel. Similarly, brands should standardize the time intervals surrounding reporting. Weekly reporting is probably too much unless you’re going to act on the information weekly. Monthly for channel reporting is probably frequent enough.
Another critical step once you have reporting standards is automation. Instead of paying for the creation of redundant spreadsheets and reports across your vendors, use an automated data dashboard to deliver all your data in a consistent format in one place with a consistent timeline. Automation will make the whole process more efficient and transfer time and energy away from data compilation and toward value-added analysis.
Finally, beyond automated channel reporting, there should be a standard approach to cross-channel reporting. We work with our clients to create cross-channel score cards that communicate overall performance in terms of business impact. We also work with our clients to ensure these measures align and integrate with larger brand scorecards. The result is that brands are able to more clearly link their digital efforts to brand measures such as awareness, sales, etc.
- Implement an optimization program. As mentioned above, data is only as important as your willingness to act on it. Action is where the value of data is realized. Brands should set aside as much as 10% of their budgets for cross-channel optimization activity. This includes deep-dive analysis to locate bottlenecks that are inhibiting response rates, structuring tests to experiment with alternative creative or functional executions to move the needle on KPIs. Firms like Google have learned the immense power of iterative testing. Pharma can learn this too, and drive meaningful lift on engagement measures like email opt-ins, e-detail completion rates, etc. This stuff isn’t sexy but it’s very effective.
There you have it – four obstacles and four actions to help strengthen your multi-channel measurement. Best of luck in your digital measurement endeavors.
- What is a KPI? The answer is iii. Key Performance Indicator. KPIs are business metrics used to evaluate factors crucial to the success of a business. Simply put, a KPI is a metric that lets you know how you’re doing against your goals.
- True or False: A unique user the same as a person?
Unique visitors refers to the number of distinct computers requesting pages from the website during a given period, regardless of how often that computer visits. Since people may access sites from multiple computers using different browsers, unique visitors doesn’t equate to specific people. In other words, the same person could be counted as two unique visitors if they access the site from two different computers. So, the answer is False.
- What is an A/B test? A/B testing (sometimes called split testing) is comparing two versions of a web page to see which one performs better. You compare two web pages by showing the two variants (let’s call them A and B) to similar visitors at the same time. The one that gives a better conversion rate wins. A/B testing is a simple and easy way to begin to improve your digital performance. More advanced testing introduces multiple variables. That’s called M/V/T, or multivariate testing.
- What is a DMP and why would you need one? A data management platform (DMP) is a centralized computing system for collecting, integrating and managing large sets of structured and unstructured data from disparate sources. The data includes both 1st party data generated from your owned media platforms and data from 3rd party data sources, such as demographic data, or behavioral data. The reason to have a DMP would be to give you detailed information about your customers to create hyper-targeted messages, which result in higher conversion rates, ROI and customer retention. For instance, a DMP could let you target your customers based on a combination of time of data, geography, previous site behavior and demographics.