5 questions to determine the success of a CMO
In this view, an effective marketing strategy in 2023 involves balancing a number of factors which, at times, may seem contradictory. However, some elements of marketing strategy will remain the same, irrespective of the changes in our industry.
Looking at many projects in a vast range of industries, our team was able to uncover five major questions that will determine the success or failure of any CMO. The ability of a marketing team to quickly answer these questions often testifies to the perceptiveness of its leadership.
In and of themselves, these questions might seem fairly straightforward and intuitive. However, the journey needed to answer them can be hard to follow, especially if the company’s data culture hasn’t reached a certain level of maturity.
The challenge is to obtain and organize data, then develop analytics solutions capable of responding specifically and coherently to your challenges. With Adviso’s research and development team, a series of solutions were developed to support our clients at each of these steps. In this article, we’ll present these approaches and their main underlying concepts. We hope to inspire you in your approach to your own marketing analytics infrastructure so that you can effectively respond to these five basic questions for your CMO. In a sense, this is a way of creating an analytics tool box adapted to your needs, irrespective of your business domain.
2. How do you know which markets contain opportunities?
Knowing when to invest your marketing budget is one thing. Knowing where to invest it is another. Certain tools can be used to identify emerging markets, but often these tools don’t take into consideration a company’s specific business context. That’s why our team developed an analytic model that integrates the same variables as for the annual planning model above. However, instead of measuring the size of opportunities over time, this version measures the size of opportunities by market.
For example, one of our clients sincerely believed that the majority of the budgets should go to Alberta, the reason being that the percentage of revenues from this province was the highest. However, our model detected two factors that the client hadn’t considered. First, demand in Alberta had been gradually declining year after year. Second, competition was becoming increasingly fierce, which meant that acquisition costs were sharply increasing. On the other hand, other markets such as British Columbia were experiencing strong growth in demand with each passing year, while at the same time competitive signals were relatively weak. This made the province an interesting niche for investment by our client.
After performing A/B tests with our media team, we noted that following more aggressive investment in British Columbia, conversions were significantly higher and acquisition cost had sharply lowered.
3. How should our marketing channels be allocated?
In this era of disappearing third-party digital identifiers, knowing how to allocate your marketing budget is not as simple as it used to be. Attribution models by e-commerce platform (Google, Adobe, etc.) only show a portion of the truth. That’s why the industry is returning to statistical inference techniques. Amongst other methods, marketing mix modelling (or MMM) is making a big comeback.
For traditional marketers (radio, TV, outdoor), MMM use dates back a few decades. But for digital marketers, this attribution technique is still very new and even theoretical. The challenge with these models is learning how to better integrate digital and traditional marketing in your planning. Also, to truly know which channels bring the most incremental value to all of your business results, it’s important to also consider factors that are specific to the company. To this end, the marketing team must work in close collaboration with its business intelligence experts, as well as its operations division, in order to correctly identify the variables relating to the performance of your company.
4. Which consumers should be prioritized in our segments?
The disappearance of third-party identifiers has rendered first-party customer data more important than ever. Marketing teams can no longer entirely rely on user data from Google and Facebook/Meta to handle the targeting of qualified users. Lookalike models, which enable Google and Facebook (or any other platform) to find users that resemble your best purchasers, are tactics that are about to disappear.
In this context, what can you do to continue to segment the targeting of your consumers? The R&D team at Adviso has developed a few approaches, since every client is different. But the most important is to establish two analytics frameworks based on your customers:
1. A behavioural framework: This could involve all the behavioural data such as basic metrics in Google Analytics, your engagement platform for email or your CRM. The idea is to model the purchase behaviour and engagement in a way that’s intuitive for our business.
2. A business framework: This involves a way of cross-referencing the behavioural model with your own business rationale. Identify the business metrics that are the most relevant for interpreting your customer behaviour.
Adviso uses the model from BJ Fogg, PhD, amongst others, as a model for taking action based on a behavioural framework and a business rationale. But the specific model isn’t important so long as you focus on “why” and not “how.” To read about a few more concrete examples and for deeper technical details, take a look at my scientific article on the C-3DP technique, for example.
5. How much should we invest to achieve our objectives?
Finally, after answering the questions above, the biggest question you should ask yourself is the following: How much do we have to invest to achieve our objectives? At this stage, too many companies get involved in a kind of wishful thinking, in that they throw a few numbers in the air to determine the growth and investment required, then cross their fingers and hope they make it. This way of going about things is very dangerous and costly in many cases.
For this reason, Adviso’s R&D department designed an analytics technique called “KPI reverse engineering.” Essentially, without getting into too many technical details, the idea is to evaluate through an analytics exercise whether the difference between growth objectives and marketing investment is realistic or not. In addition, this technique combines standard techniques in predictive and projected analytics. This is accomplished in part by projecting the organic growth of a company in relation to the effectiveness of its prior marketing investment.
If the gap is too large analytically, our team recommends lowering the growth objective or even adjusting the marketing budget upwards or downwards to hit the target. This is not an exact science. However, after many years of observing many of our clients’ sectors of activity, we’ve noted that such an exercise empirically brings added value. In some cases, the difference in marketing performance after KPI reverse engineering can be as high as doubled growth.
Of course it’s not necessary to adopt our technique. The takeaway is that it’s important to model your growth in relation to your marketing investments.
With all the coming marketing challenges that will emerge by 2025, our main suggestion is to start orienting your overall marketing strategy around these five questions. They will provide better grounding for your team from year to year while also serving as an improved compass for your activities. For a CMO, these five questions essentially allow you to determine and maximize what really matters.