Can you account for where every contact or sale a customer makes with your organization comes from? This is one of the big challenges for CMOs; no one can attribute all revenue with absolute accuracy.
As Bob Evans from Oracle points out, attribution is a major issue for CMOs. Understanding the precise channels and numbers for which to give credit for sales helps to drive conversions.
How much extra credibility does this bring to your marketing team? Well if you’ve ever been the butt of jokes about “marketing are going to get their crayons out”, you’ll know that any time marketing can back their ideas with solid data is a win that helps solidify their seat at the decision-making table.
The more accuracy you have with attribution, the better for you to present your marketing activities as a “hard science” rather than a somewhat hazy stab in the dark which leads to those jokes about what it is that marketing gets up to.
In a world where marketing is facing increasing pressure to up their accountability beyond qualitative measures, data-driven marketing is the key, so what should CMOs be looking out for?
Effective Use of Data
Interestingly enough, while a McKinsey and Company survey found that the ability to make data-informed decisions was a high priority among organizations, only 10% felt that they used customer insights effectively and fed them back to the business to improve performance.
Where does the disconnect happen? There are a few reasons why the use of marketing data may be ineffective:
Algorithms Aren’t Perfect
As stated by CMO, how to determine where credit is due is the major challenge for correct attribution. You may be using an algorithm to assist with attribution, but no one algorithm will be entirely accurate.
“The most effective solution to solving the attribution conundrum comes from leaders in predictive modeling. Rather than rely on a single algorithm to measure attribution, marketers can take an “ensemble” approach that uses multiple algorithms.”
This “ensemble” approach to gathering data is really statistical science. If you pull together multiple predictions from different sources, there is a higher likelihood of accuracy than using one.
In fact, CMO tells us that ensemble attribution can improve predictive accuracy by as much as 35% when compared to using a single source.
“While a single-model methodology may work for a set amount of time or circumstances, the ensemble method adapts to changing market or business conditions.”
Omni-Channel Can Be Complicated
How do you attribute your mix of online and offline activities? This can be a complicated prospect, though technology is ever-developing to provide more advanced tracking and models for attribution.
It’s not just a question of attribution however. With so many new tools and channels becoming available to marketers all the time, it can be very tempting to go down the “do it all” route and see what sticks. This can cause marketing efforts to suffer from a lack of focus though. If you’re spreading resources too thinly in order to cover more channels, your insights are going to be limited.
We knew of one company who experienced this first-hand. They created an exciting new app with the potential to really take-off in the small business sector. Of course they wanted to get it as much exposure as possible — they were proud of what they had created and felt it could make a real difference to people.
When it came to marketing, they did initially try to do (by their own acknowledgement) too many things. They were a small team with limited resources, so trying to be on five different social media platforms, paid online and offline advertising, as well as unpaid efforts such as guest blogging became an incredible tangle. They had little idea how to attribute the customers they got and they knew that efforts on some channels could be better, but were hampered by not having time or resources.
McKinsey and Company warns of this phenomena which diffuses focus and creates coordination issues. Indeed, this company found that “less was more” and that not only were they better able to attribute their customers gained when they narrowed focus, but their overall effort on each of the channels they chose was more effective.
Connect to Decision Makers
Marketing analytics are about adding value to your organization. They give you a seat at the table with a clear connection to company results and allow CMOs to take responsibility for marketing-based revenue growth (something which Bob Evans proposes will become a common KPI for CMOs).
A big challenge faced by CMOs is that there is now so much data available, the real nuggets can become bogged down in the quagmire so that it is difficult to see real results. A group from McKinsey and Company discussed this problem in an article for Forbes:
“In our experience, companies often address this problem by trying to analyze ever greater data sets in an effort to uncover a killer insight. Or they look for a tool that can solve every problem. But the core issue is that many analytics efforts remain disconnected from key decision makers.”
The disconnect they talk about can happen when data is simply too complicated. To give effective insights, it needs to be understandable to the key people who will action the data. As they say, if the data at your company has been put together by a brilliant data scientist, however nobody else can understand the modeling, then the chances are it is ineffective for the purposes which marketing need it.
What are the vital questions which executives must have answered by marketing analytics? This is where the connection needs to be made. While there are more tools than ever available for providing marketing analysis, surprisingly, studies show that only one in eight CMOs consider that they are part of a data-driven organization where an analytical culture is fostered by senior management.
Kissmetrics point out that an overload of data can often get in the way: “Try as we might to wring measurable, impactful details on our customers from the information we collect, there’s just too much interference and noise clogging up the connection.”
Having good analytics tools which are simple to use and provide the data you really need to make marketing decisions is a good place to start. Data should be centralized and harnessed to create marketing plans which are highly targeted.
Going back to McKinsey and Company: “applying analytics effectively can allow companies to free up 15-30% of their total marketing budget.” Enough to convince decision-makers? We think so!
Attribution and effective use of marketing analytics are major challenges for CMOs. The fact is that omni-channel environments can be tricky and data modeling is never perfect.
However, if CMOs can make better use of the wide range of information they get and connect data to the things which really matter to decision makers, they are more likely to get better buy-in and a seat at the table.
This might mean asking for better high-level data which allows executives to see overall information, such as how to maximize return on overall spend. Analytics on tactical issues are important too, but you need the right mix to ensure that the information presented is clear.
Koombea can help you to turn your data insights into the experiences your customers are looking for. Get in touch with us for your app needs.