Daniel Smulevich, EVP Cloud at Jellyfish, explains how businesses can benefit from putting their tech and data to maximum use – and why many don’t

Like many things in life, marketing has benefitted hugely in recent years from automation – or, to be precise, technification. You want to keep all the data you hold on your customers in one place where everyone can access it? There’s a CRM platform for that. You want to know what people are saying about you on social media? There’s a platform for that too, and for almost anything else you can think of.

In fact, in my experience, the average business has around 80 to 100 tech platforms at its disposal. More than enough, you would think, to help them make a decent fist of marketing their products and services.

And yet…

Many marketers I talk to still feel dissatisfied with their company’s performance. Because when everyone has the same tech – and, by and large, most companies do – it’s like no one has it. It doesn’t deliver the competitive advantage it was bought to deliver.

So why is this? I’m convinced it’s because most marketing tech is bought, and sold, on a feature-oriented basis, and in silos. One part of the marketing department needs a particular tool to do a particular job, so they buy it, and use it, blissfully ignorant to the fact it can also do other jobs that could help other parts of the business if only they looked beyond the immediate problem they were trying to solve.

As an example, someone might implement server-side Google Tag Manager (sGTM) for its data collection capabilities but miss the fact that it’s also great for bid optimisation. Or a marketing team might choose a business intelligence tool for its reporting capabilities, ignoring the fact that a competing solution may also have native data modelling capabilities that a data science team could take advantage of.

Use company-specific data for better marketing

For a tech platform to provide the greatest benefit to your business, it needs to be powered by the most valuable data: data that is unique to your business. However, this essential, company-specific data is often overlooked.

Consider, for example, the importance of first-party data. For many companies, this begins and ends with an email address and non-personally identifiable cookie data. But every company has at its disposal, or can acquire, a wealth of other data, such as location data around where their customers live; how far from one of their stores they are; what type of car they drive; their household income.

Add to that business data, such as which products make the best margin, and category data, specific and vital to the vertical they operate in – for a travel company, that might include people’s lead time for researching holidays – and the category becomes a far more interesting one.

Over the past year, we have developed a process called the MMI Blueprint – Mix, Match, Integrate. Its entire purpose is to help companies get a better handle on what tech and what data they have, how it can be best deployed – not just to solve a local, siloed problem, but to help the whole marketing function – and how they can achieve their objectives, It’s effectively an interrogation of where the business currently is and where it wants to get to, leading to a recommendation of how it is going to get there, with technology and data at its core.

FInd the right KPIs for your real objectives

We start by asking the CMO or Director of Marketing of a brand to define their marketing objectives. Often, what we hear is that they want to make more profit. But that is not, in itself, a useful KPI, because there are so many ways that could be achieved, such as reducing media inefficiency; providing a better web experience so that more people convert; reducing churn; reducing returns; or encouraging more frequent purchases, to name a few.

So we identify the drivers that will deliver the marketing objectives. From there, we can assess both the technology and the data available to the company, to identify any areas where the tech is not being used to its full capacity; any data that is not being leveraged; and any gaps in the tech stack or the data pool to see where new investment is needed.

That in turn gives us the insight we need to arrive at a score for how the company currently matches up to its objectives in five key areas: Bidding, Targeting, Creative, Experience and Measurement. These, of course, are all on the promotional side of marketing, but in time, we plan to extend the Blueprint to cover all other aspects of the discipline.

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From here, we can see and advise on what needs to be done to improve the score in each area, subject to any legal, financial or resource constraints that may stand in the way of achieving a perfect match to the objectives.

The final step in the process is a quantification of the cost and returns of any of the actions and investments we recommend. The second element here, the return on the investment, is key, and often overlooked. If you don’t document the likely returns, and how they might be positively impacted by spending a little more, the only line item that ever comes under scrutiny is the cost, and the outcome of this isolated focus on the cost is often a budget cut.

When you’re calculating value, don’t forget time

All of this is used to create a roadmap, with some quick wins to get the key stakeholders onside. Too often, I have seen tech-focused marketing projects flounder because they set their sights too high and have no recognisable achievement milestones to show that the vision is being delivered on. The business becomes disillusioned with the project, budgets are cut, and it stalls or grinds to a complete halt.

To prevent this, we use the concept of Time to Value, which recognises that the cost of a project and the value it delivers don’t live in isolation from the time taken to deliver it, so we tailor our recommendations based on what the client needs the payback to be, and by when.

As a simple example, we could build a complex model that delivers a value of 100 at a cost of 30, but takes 12 months to be ready, because it will require a high level of alignment of people and systems. Or we could start with a model that delivers lower value, but is also less expensive to implement and can be activated in three months – and then move to a second phase where we spend that cost of 30 to deliver the remaining value over those additional nine months.

In the latter example, the client may be spending a bit more money, but they get value faster, so they are able to realise some benefits in year one, rather than waiting an entire year.

The recommendations that the MMI Blueprint produces vary from client to client, but are not always massively complex and may not always appear groundbreakingly new. One output could be a Customer Lifetime Value model, for example – hardly a new concept, but the difference is the way in which it is designed to work with the platforms and the data you, uniquely, have at your disposal.

All too often, where marketing tech is concerned, that’s not the case.

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