The Five Biggest Data Driven Marketing Mistakes

You want to use data to drive your digital marketing efforts forward. But there’s something that isn’t working or you don’t know how to go about doing it.

Here’s what I believe to be the top challenges facing businesses today when it comes to data driven marketing within organisations that wish to be data-led.

1. Thinking technology will give you the answers

It won’t. I’ve seen countless companies with top end enterprise analytics systems struggling to use them.

For every pound per year you spend on marketing tech, be prepared to spend at least as much on hiring people who know how to use it.

2. Not concentrating on key metrics

There’s a temptation to track everything under sun because we can. All that will do is leave you sitting on a heap of data and not knowing what to focus on first.

Instead spend time understanding what data you need in order to be able to take immediate action that results in a better experience for prospects or customers and therefore improves the chance of them doing business with you.

3. Not have technical skills within your marketing team

Once you knew what you need to track, how are you going to get that implemented on your website?

You need technical people within your marketing team who are comfortable talking about HTML, JavaScript and SQL. You should also have a Data Scientist who is familiar with statistical modelling and exploratory analysis techniques. Knowledge of R, SAS, SPSS or similar packages is useful.

They will be able to assess what can and can’t be done, and clearly convey your teams needs to the IT team. And they will also be able to spot interesting patterns in the data that allows you to act.

Without this type of resource getting anything done will take much longer.

4. Storing data in silos

There’s little point having your dream team in place if they can’t get access to the data they need in a timely fashion.

The biggest hurdle I often see is companies storing data in disparate systems that don’t talk to each other.

  • The web analysts use Google Analytics and Adobe Sitecatalyst to look at on site behaviour.

  • The email marketing team are building lists from a CRM tool like Salesforce and then analysing the results of their campaigns (open rate, click through rate, deliverability) in their email vendor’s software.

  • The Acquisition team are looking at display campaigns in Doubleclick and PPC in Facebook, LinkedIn and Google Adwords.

  • The data scientists are studying data collected into your companies data warehouse.

  • The finance team are looking at profit margins and revenue in their financial systems.

This is a massive issue. To do the analysis that will truly have an impact on customer lifetime value, revenue and the profitability of your business in the long run you need to be storing this data in one place that anyone within the business can access at a moments notice.

I’m not saying putting the infrastructure in place to do this is easy. Not by a long shot. If it was everybody would be doing it.

5. Reporting not doing

The whole point of looking at data is to find insights that allow you to take action.

Don’t spend hours building beautiful reports that just report on historic data, people look at, but don’t do anything with.

A recent client was sending out 90 reports to people within their business every week. After a survey they realised under 30 of these were actually being looked at, and of those only a handful were used to change marketing activity or site content.

Cut out the crap and start looking at a handful of metrics. Improve those metrics. Then choose another handfu of metrics and work to improve those. Continue until you retire.

Not only does this make you more effective at delivering results that make a difference, but you also save time and money on system implementation costs (because you aren’t fooled by the latest all singing all dancing pretty looking marketing technology ever year).

Ed Brocklebank (aka Metric Mogul) is an analytics and digital marketing consultant. He helps business of all sizes become more data-driven through measurement, strategy and activation. He works as a Strategic Analytics Director at Jellyfish in London, as well as delivering training on behalf of Google and formerly General Assembly.