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Data, Insight, Action! From marketing data to results in 5 steps.

by Simon Spyer on Jan 29, 2014 9:00:00 AM

“Big Data” passed the acid test in the marketing space when agency planners starting to talk a good game on data empowering brands. Data, Insight, Action: use your marketing data to deliver better results

While customer understanding and centricity are the very foundations of marketing itself, marketing departments have had to start thinking about their data solutions (in their widest sense) and the data strategy behind them.

It may not sound the most glamorous of marketing activities but it has become an absolute necessity for brands that expect their marketing investment to payback (ROMI). But it shouldn’t be a daunting task and by following these steps you can start becoming more customer-centric and understanding the return on your marketing investment.

Step 1 - Understand what a data strategy is and what it means for your marketing

A data strategy connects your marketing vision and brand plan to your data capability. Your data capability encompasses how you and your team use or will use your data to enable your marketing vision by understanding your customers so well that your product or service sells itself.

This capability should be broken down into 4 parts:

i) Processes - the data insight and customer analytics that will be required and the actions you will drive from this learning to deliver better customer experience.
ii) People - the people that you have and will need to use your information, both in building your knowledge base and in applying this knowledge, testing, measuring and iterating. 
iii) Data - the data that you have and the data that you will need to capture to make your plan reality and the quality of data that you are capturing. 
iv) Technology - the systems needed to knit your data together, organise it, analyse and then apply it. Applying your data will encompass all of the processes that you have defined above (and will include reporting and marketing campaigns, events and triggers). 

Step 2 - The data lifecycle

Just as you have a customer lifecycle (or customer journey) so will your data.

You can keep the data lifecycle simple and break it into 3 stages:
  • Obtain - what data do you need to collect and what is the value in collecting it?
  • Share - how are you going to share the data, who does it need to be shared with and how often?
  • Apply - what are the key customer-facing actions that you need to drive?
Then, thinking of processes, people, data and technology, map your requirements for each stage.

If you already have a data strategy or feel that 3 stages are too simplistic then consider adding additional stages such as validate, maintain and dispose.

Step 3 - Governance

Hopefully, so far, building a strategy for your marketing data feels more straightforward than you feared.

When we start talking about data governance, it’s very easy to switch off and think that the job is done.

If phrases like “multiple versions of the truth” sound familiar or you spend time in meetings debating how something was calculated or where the data was sourced from, then it’s imperative that you don’t ignore this step.

Your data governance binds all of your data planning together and ensures that it is used consistently. Much of its focus is on the application of your data and making it consistent.

The aim of your data governance should be to enable the People that you have defined to focus on taking data-led actions (whether it’s tweaking a marketing campaign or completing a new piece of analysis for example) rather than worrying about whether they understand what the data means or questioning its quality.

Focus on:
  • Creating a data dictionary
  • Standardising your metrics and how they are calculated. Of course, make sure that you link these metrics to your KPIs and marketing plan.
  • Defining who is accountable for your marketing data (who ‘owns’ the data is makes the final decision on how it’s used) and who is responsible for it (maintaining it, using it, applying it) 

Step 4 - Start with the customer

The basis for your data strategy will be your ability to secure customer data. You may already have rich transaction data linked to individual customers but how can you augment this with richer data about the individual, where you brand could play a role in their life and how you could be personally relevant to them?

You need to build a clear value proposition and ensure that it’s simple for a customer to understand what’s in it for them. How will sharing more information with you help improve their experience or allow you to serve them better?

Step 5 - Getting started 

Creating a data strategy for the whole business might feel daunting and time consuming. Start with building one for a business area, like Marketing, which will have a measurable impact on customer experience and business value.

As with all advice that we give:

  • Be pragmatic
  • Start small
  • Set key principles
  • Agree the quick wins and big hitters and make a start

 

A data strategy should be an integral part of your marketing strategy and these steps should help you to breakdown what a data strategy really means for you and to start making it happen. Please share your experiences of building a data strategy and whether it help you to improve your marketing performance.

 

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This post was written by Simon Spyer

Co-founder & Insight Partner at Conduit, professional insight-monger, dad, lover of all sport and Spurs.

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