Geoff Wolf, EVP Client Strategy
For many marketers reading this column, data is fun! We love the challenge of figuring out how to find and use data to solve problems and drive all kinds of marketing initiatives.
However, we also operate in a business environment and have to ultimately answer the question of value. How do we create true value using our expertise and experience?
Let’s look at four key elements needed to understand how data metrics create value.
1. The Foundation to Establish Value
Data metrics are a measurement process that enables us to provide visibility of data moving from Point A to Point B. The process starts with an awareness of exactly what you will be measuring. It is critical to understand from the very beginning of a measurement process what actions are intended to be taken once the measurement is complete. This means knowing how the results will be used.
What value do the key performance indicators (KPIs) represent? More specifically, how is that value created? Some examples of creating value are driving sales, impressions, lead generation or perhaps quotations. Another example might be reducing a specific cost element. Data metrics are what defines where you are today, where you intend to be tomorrow, and what movement has to happen to get there.
For example, if you want to grow your email list to add more people reading your emails, then the key metrics will include the number of people who sign up on your list and how many open emails, click through to a landing page and spend time there. All of these data points are the building blocks necessary to drive more people to actually read your emails.
2. The Metrics Most Important to Your Brand
There are some data metrics that all direct marketers share. Certainly, attribution, segmentation and having enough scale to generate acceptable confidence factors are some common metrics. More importantly, every brand has unique elements that drive its success. Spend time focusing on the unique ones. You need to determine what unique KPIs matter to YOUR brand.
Think about this in terms of what really drives purchase behavior, or the action you are seeking if it is not an actual sale.
An example might be a typical sales force-driven business model. It is common for a brand that started and fueled its growth through sales force relationships to get distracted over time with print mailing, website and even retail store metrics. However, if one really looks at the data, both transactional and research, they may find that no matter what media is pushed out to the market, the result that matters is the sales force interacting with the customers.
While the actual cash sales may arrive via check, Web orders, POS cash registers or the sales force writing up orders, it is the role of the sales people that matter to the brand. In this case, a set of data metrics must be developed to measure sales force touches with the marketplace.
3. The Ability to Inform Marketing strategies
Transactional KPIs to inform a business on how different marketing channels contributed to overhead/profit
The most common value is establishing a ROI of some type. To the left there is a chart of data metrics that use common transactional KPIs to inform a business on how different marketing channels contributed to overhead/profit and how they compare to each other. In this case, average order and margins were held constant while allowing the variable marketing expense to reflect real media channel costs.
The resulting differences on contribution between media channels help inform management of what levers they can pull to influence results, as well as what strategic decisions must be made to meet their investment objectives. Action can be taken to enhance value through merchandise price points and margins. Or, management can choose to invest more in a particular media channel.
4. The Effectiveness as a Process
Until recently, data metrics were served up as snapshots in time. Analysts would create a report that informed us about a specific set of questions. If we wanted additional views or questions answered, or even the same views for a different time period or media channel, then another report would be generated. Technology has become a very powerful tool when it comes to data metrics. We can now load up a database with relevant data and connectivity between records that allows an ongoing process rather than a static reporting tool. In addition, this can be served up in real-time to the extent the database can support this advanced opportunity.
Some common data metrics can be set up to allow management to interact with the data as a process. Perhaps in a weekly meeting, discussions can be supported by an analyst to look at 1) customer acquisition by first order channel; 2) the number of months (or any other timeframe for that matter) it took to acquire these records; and 3) contribution of these new customers by quarter. One could also add views of the prior year, first order amount or any number of other relevant data metrics to these discussions.
The main takeaway for data-driven metrics is that they need to be used in an ongoing process to inform strategic discussions. Specifically, the process to inform starts with capture and normalization of data, is followed by a query and discovery stage, and finally action is taken. The future of analytics is using discovery to inform strategy.
As published in Target Marketing magazine, December 2014.
Tags: analytics, data, Geoff Wolf, marketing, metrics, Strategy
