MAP to the Future: Four Steps to Drive Value from Your Data

(Europe) Modern digital marketing and data management are driving increased spending on analytics, but many organizations still struggle with the sheer scale of possible data inputs.

Evolving customer experience (CX), expectations and technology combine to create a confusing landscape. That leaves the field of data analytics ripe for transformation to give companies the tools they crave and drive revenue from data they collect in the form of valuable insights.

So, how can business leaders transform their organizations, and begin to realize value from the data and analytics they have long been promised?

How to get the boardroom on board

Nothing gets off the ground without leadership buy-in, and approaching the board with your plan takes thought.

The whole point of a data strategy is to support the business in achieving its overall strategic goals. So, you will need to demonstrate your strategy is both born from the wider goals of the business and aligned directly with them.

In general, this begins with writing the data strategy to fix an identified problem. In this way, you can build up your data strategy to solve the key blockers that stop your company from achieving its goals. That will be much more successful than trying to define an all-singing, all-dancing data strategy which is not connected to the day-to-day issues that employees and customers experience on the ground.

For example, a good data strategy will mend the problem of untargeted communication that treats existing, even loyal, customers as new. Better data will lead to more relevant advertising and customers who do not get annoyed by messages that are meaningless to them.

If you focus your strategy around resolving real business problems and helping drive forward customer use cases that are top of mind for the C-suite, it will be much easier to gain boardroom buy-in on your strategy.

A four-step data strategy that works for your business

Now that you have persuaded senior leaders that your strategy is strong -- and affordable, it is time to prepare to make changes that will add value to your business long into the future.

Demystifying data management is a sensible place to start. The good news is there is a four-stage process to help you get a grip on all of the data at your disposal.

Stage 1:  Unify data with a single customer view 

With today’s avalanche of omnichannel customer data, garnering actionable insights from fragmented customer experience can paint only part of the picture. Completing it requires breaking down data silos and creating a unified, single view of the customer.

A single customer view provides marketers with data they can trust, future-proofing customer data based on robust data quality, real-time insights and simplified integrations.

In a recent CMO Survey conducted by Credera, 34% of CMOs said, “Aggregating and connecting unique identifiers to each customer from individual interactions across different data sources” was the main challenge they faced in delivering an effective customer experience. 

The process of unifying data in this way can be achieved in three steps:

1. Analyze what data you do have and where it is:  This step is often overlooked but can often uncover data troves you didn’t know existed.

2. Define what data you think will be most helpful for your use cases:  This helps to break the problem down. Too many companies make the mistake of trying to bring all their data together into one place and then are left wondering what to do with it. Some ideas of key data sets that you might want to start with: customer records, sales data, ecommerce, website logins, email sign-ups and call center records.

3. Start to bring your customer data together:  We would advise not worrying too much about the technology at this early stage. Bring the most valuable data sets together wherever that makes most sense for your company; this might be a database, a data lake, a customer data platform or even an email marketing tool.

When we said not to worry too much about the technology early, the key point was to get some wins on the table and gain some confidence that bringing together your data is going to provide measurable benefit to your company. Once you have done that initial test, then it is time to focus on the technology so the fourth stage would be the following.

4. Define your technology roadmap: This can often be done in parallel with the steps above. We would advocate thinking about data and use cases first and then technology alongside. This makes it easier to ensure you procure only the platforms your company needs and not fall into the trap of procuring all the shiny tech vendors software that promise will solve all your problems.

Stage 2:  Use a marketing analytics platform to create micro segments

Modern cloud data platforms, specifically a Marketing Analytics Platform (MAP), enable marketers to accelerate time to value, and deliver differentiated precision marketing.

While organizations have traditionally relied on second- and third-party data to build customer segments and marketing campaigns, its availability is rapidly declining.

Recently, consumer digital privacy concerns have fueled restrictions on capturing and sharing third-party data:  96% of Apple iOS consumers opt out of ad tracking, while Google has replaced third-party cookies with Federated Learning of Cohorts (FLoC) technology, for example.

Since access to external (second- and third-party) data is shrinking, it is essential for organizations to collect first-party data about potential customers in order to deliver more meaningful customer experiences.

You should start experimenting with creating segments and audiences from your first party data to enhance your existing marketing and prepare for a world where third party data will be much harder to come by.

Stage 3: Develop a decisioning engine

The next stage would be to add in a decisioning engine which will enable you to turn your actionable insight and valuable audience segments into next best actions.

A decision engine will allow you to create models based on your consumers’ behavior and define the most appropriate next action. Getting this right is key to delivering a truly exceptional customer experience.

As customer expectations for your company’s interactions increase, having confidence that you can deliver tailored experiences in real-time is more important than ever.

A key benefit for using a marketing analytics platform to enable a decisioning engine is high-quality data ingestion, along with the ability to create and leverage external machine learning models that elevate the decisioning engine beyond “if then”-style rules.

You should also set up multivariate testing at this stage. This is the evolution of A/B testing where you test multiple customer experiences at the same time with your customers and automatically move to the most effective experience over time. This obviously links with the next stage which talks about the importance of measurement.

Stage 4: Measure and refine

The old analogy that you cannot change what you cannot measure is even more important now. In order to understand how to adapt your strategy to the changing needs of consumers, you have to understand what is working and what is not.

The faster you can make the feedback cycle from learning to adapting, the better your marketing and your entire organization is going to perform. Those that can move the fastest will be the leaders of the future.

Through effective implementations of a cloud-based MAP offering, and integrations with downstream channels, we have witnessed organizations increase customer lifetime value by 20% and decrease cost per action by 30%.

About the Author

Josh Nicholson is a Managing Director and leads Credera’s UK MarTech practice in the South of England. He is an experienced technology advisor and program manager with deep expertise in data and marketing technology. Nicholson has a broad range of experience across consumer goods, retail, financial services, and public sector clients. He has a passion for delivering excellent customer experience and thrives on helping clients solve some of their most challenging problems.

Nicholson graduated from the University of Bristol with a master’s in Computer Systems Engineering. He holds qualifications in Scaled Agile (SAFE), TOGAF, Product Ownership, as well as public cloud certifications.