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August 29, 2016 Defining a data strategy: What, where & when Mike Fahey, Executive Vice President

Defining a data strategy: What, where & when

Do you know the difference between a lake and a warehouse? A warehouse is a fixed set of structured data, a lake is a more agile collection of often unstructured data. You can get lost in a warehouse looking for what you want, if the item is indeed in stock, and you can quickly drown in a lake while thrashing round looking for help. 

Big Data opportunities have grown significantly over the last few years and businesses are starting to see the fruits of a maturing industry around the collection, combination and interrogation of data. However, as is often the case, new challenges have also appeared alongside the opportunities. 

Aside from the traditional difficulties, such as getting users to share their data, ensuring it's accurate, and synchronizing different systems, there are increasing concerns around privacy from the public, and an impending new EU law on data protection that will have significant impact in to how organizations use data.

Given the numerous challenges and opportunities, it's more important than ever to consider the What, Where and When of your data strategy.


Users will only complete a limited amount of data, so considering what you require is important. Every company objective has a minimal viable amount of data to be achievable. In online recruitment it’s often a user's job title, location and salary. In dating it’s age, location, preference and gender – and arguably location isn’t as key these days.

Your business will have several minimal viable data points and establishing these are key to understanding what constitutes a useful user profile.

When it comes to designing the different data capture points in your system, consider the following research from the DMA:

  • 58% of users say whether they trust a brand is key to doing business.
  • 90% want more control over their data.
  • 80% believe companies get the most benefit out of them sharing their data.
  • The mere mention of 3rd party marketing, even where you can clearly opt out, suppresses opt-in rates for 1st party marketing and can damage brand trust.

Building trust with your audience is clearly important and, if most users believe you benefit more than they do from data sharing, considering what services you offer a user can significantly impact conversion rates.

Under 2% of traffic 'registers' on a job board, most users instead sign up to a service. 

Providing clear benefits in return for data will result in higher conversion rates, which is why the average job board gets more job alert creations than hard registrations.


To maximize the amount of data you collect about a user, you should consider all the touch points on your site. Collecting lots of data from different areas will provide a greater benefit than having one large registration form. These only reduce your conversion rates and provide inaccurate data as users rush to complete it.

A login barrier reduces conversion rates by over 50% on key actions such as course alerts, job alerts or applications

Where you collect data will become more important with the new EU Data Protection Law. The concept of “implied consent” is being removed and instead consent must be specific, informed and freely given.

This is a much more granular and unambiguous approach to marketing preferences than we previously have seen online and it’ll be interesting to see how the laws are implemented. 


Collecting data is relatively easy. Interpreting and understanding when to use the data is where competitive advantage is gained. 

Increasing your site engagement is something I’ve written about previously. Data is absolutely key here in informing your decisions. It allows you to market services that are of use to your audience, understand what works and what doesn’t, and can provide a complete picture of your supply & demand.

The other area where good data can make a huge difference is around selling. In recent years the concept of data lead selling has become more prevalent, as buyers grow to be more sophisticated at establishing an ROI of their purchase.

Detailed and accurate data can help you build sales stories, increase confidence for the buyer, and assist the sales person in providing consultancy to their prospect on what to purchase.

Having a data lead sales and marketing strategy reduced cost of acquisition by 30% for Incisive Media recruitment

There are some common traits around the way people react to data that can help when selling:

  • Statistics and numbers impress people, which is why we see them so often in election campaigns.
  • Statistics and numbers are rarely questioned, which is why we see dodgy numbers in those election campaigns - Brexit Leave, anyone?
  • People relate to statistics more if there is a story around them, an anecdote or a tale.
  • There are always psychological influences at play that can counter a data story, such as pre-judgments people make over the value of an item.
  • Uncertainty in your data, tone or story undermines a sales story, so having the right facts at hand is critical.
  • People have a tendency to find patterns in data, even when they are absent.

Data usage is only going to increase over time, allowing sites to engage and understand their audience more, and giving the buyer of your services the power to really drill into the ROI you offer.

Billions of digital transactions happen every second, composed of emails, shares, comments, job applications, and more - all generating potentially useful data for your business.

It's a great opportunity for sales and marketing, regardless of if you store that data within a packed warehouse or extremely flooded lake.

If you'd like to discuss the what, where and when of your data strategy please get in touch.