Brands are continually evaluating how they can better qualify the impact of their marketing activities. The marketers themselves, acting under tighter budgets, are increasingly needing to demonstrate the value of campaigns from a customer engagement, revenue contribution or business outcomes perspective. Marketers must measure and optimise as much as possible while testing, learning, and adapting their campaigns and activities based on insights.
As such, brands can best prepare for performing such marketing measurement activities by understanding first-party data (the information they collect directly from customers); using technology to enable the brand to develop successful campaigns; and investing in human capital.
Coming to terms with first-party data
Having the right data is key to any successful marketing activity. And yet, many brands still invest in third-party data sources as opposed to relying on the information they already have at their disposal. In fact, company first-party data provides an invaluable way for a business to pivot more rapidly to changing customer requirements, including respecting customer privacy and trust expectations.
Brands can use this to evaluate its marketing investments more effectively. By measuring and attributing credit across the channels where the most success is achieved with target audiences, marketing teams can quickly identify what is and is not working across complex customer journey’s involving many touchpoints and channels. Equally important is uncovering new segments that would otherwise have remained unknown.
Attribution methods that go beyond the traditional and combines rules-based models together with accessible data science methods, can surface up hidden insights that are invaluable to the marketer.
Technology as an enabler
Technology delivers the vital bridge between the business decision-making process and how this translates to a positive impact on marketing. Executives do not make decisions based on data – they require insights that can only come if first-party data is exploited to its full potential.
This is where the likes of artificial intelligence, machine learning, and data analytics get the opportunity to shine. For instance, automation based on machine learning algorithms can help garner insights while marketers can focus on achieving their strategic objectives. With technology as a foundation, organisations can make more intelligent decisions and adjust marketing activities as required.
A human approach
The third component is a focused investment on the human capital required to affect marketing change. Even beyond marketing, all business teams depend on insights to be better at their jobs. However, all team members must understand and commit to the importance of embracing data.
It is as much about speaking the same ‘data language’ as it is to collaborate to deliver better marketing initiatives. Along with this comes the importance of understanding the data being presented. Having data science teams in place mean little if the marketers (and anyone else) are not able to understand the insight being created.
This is where continuous investment in skills development especially from a data literacy perspective can help unlock significant business value.
The marketing future
From a marketing measurement perspective, each brand starts from its own, unique position. Some might just be dipping their toes into becoming data-driven, while others are more advanced in their journey.
For the former, the business must temper its expectations. There is a lot of hype around the potential of analytics and data science, but the reality is very different. A distinction must be made between the vision of executives versus what can be accomplished. As such, analysts must use a variety of methods and present the data in a story-driven manner for people who do not have such a specialist background to make the right decisions.
More advanced companies can look at things like neural networks and reinforced learning. Even so, interpreting data is key. As such, these businesses can use analytical scores to help achieve better customer results. By combining data visualisation and data science through machine learning, data becomes easier to interpret, but a foundation of data literacy must be in place to understand all this.
For any organisation, marketing measurement is the secret ingredient to helping build a better customer experience. This measurement provides the link between the business questions and the decisions the brands must make.
