Harnessing data in the digital economy is a hot topic for marketers, but it can also be a significant challenge. With endless data streams available and significant investment required, setting out on a data journey can be a daunting task. Here’s my advice to help you avoid some of the pitfalls and ensure you get maximum return from your investment. 

1. Start with the data strategy

It is essential to have an underpinning data strategy that articulates a clear vision and approach for driving business growth and profitability. This data strategy should dovetail with the business strategy to maximise its impact. Whilst it is tempting to dive into the data you have readily available within your organisation, stay focused. Start with the business questions you need to answer, taking a broader view, and build your data strategy from there. Never lose sight of the end goal which is to learn from the data to make more effective marketing decisions that improve business outcomes. 

2. Assemble a diverse team

The successful implementation of a data strategy requires a highly diverse team and skillset, comprising of business consultants to ask the right questions, data architects to design how data should be ingested and stored, and data scientists to extract knowledge and insight. 

A key objective of the data strategy is often to connect disparate data and break down operational silos. Having a wider team, representing different disciplines or departments (for example finance, marketing and research) means better input into the strategy and greater opportunity to implement results across the whole organisation. 

Given the strategic importance of data capability to businesses today, and the difficulty securing funding and affecting change, an executive sponsor can help clear the path for the successful and speedy delivery of your data strategy. 

3. Build the data framework around the consumer journey 

In today’s digital world, there are more complex relationships between brands and consumers, with the consumer journey now seamlessly scaling paid, earned and owned channels, both online and offline. In the retail sector we commonly see offline media like TV driving online sales and also “web-rooming” effects where consumers research online and ultimately buy in store. These more complex consumer journeys require an analytics approach which links the online and offline parts of the consumer journey. 

From a data management perspective, touch points from across the ecosystem should be represented, capturing both online and offline parts of the consumer journey. This could include online video views, Facebook likes, website visits and in-store purchases. Media will need to be effectively tagged to enable measurement, so ensure your digital marketing teams work closely with your media agency and analytics provider to tag your digital assets. Tagging through one central ad server maximises the insights that can be drawn from digital analytics.

In addition to relevant media data, collecting other brand data such as distribution, price and competitor activity will provide a fuller picture of performance which can be used to leverage a competitive advantage. The Holy Grail of marketing effectiveness is holistic and connected analytics and optimisation that links all media along the consumer journey. Setting up a data framework that can facilitate this is a worthwhile investment.

4. Build models to optimise marketing investment 

Building models that can optimise the marketing budget will make the results more actionable to the business. There are many techniques, including marketing mix modelling and digital attribution that enable the marketer to measure the impact of media. The strength of marketing mix modelling is that it can evaluate the role of both online and offline media in the context of external factors, including price, promotions, and distribution. 

Digital attribution on the other hand is well equipped to address a range of digital questions, such as identifying inefficient parts of the online journey and the varying effectiveness of different keywords for paid search. In response to this, marketers are increasingly using a ‘total attribution’ approach, utilising both techniques to provide holistic marketing evaluation for our clients.

5. Make it accessible

Implementation is notoriously one of the most difficult parts of the data journey. Whilst the data ingestion, processing and analytics underpinning a data management platform may be vast and complex, if you want people to use it, the output must be simple, actionable and clearly communicated. Data visualisation can help significantly in this regard, providing decision makers with data and analytics output in a timely and accessible way. Including forecasting and optimisation that clearly illustrates the potential upside (or risk) associated with specific marketing decisions will also facilitate the translation of data related insight into positive business outcomes. 

Getting maximum value out of your data is complex and will take time. Building the infrastructure, team and processes will get you half way there, but don’t forget that action and outcomes are driven by people making better marketing decisions. The better communicated your insights are to the right people, the greater the commercial outcome is likely to be for your business.