How to conduct a data audit

As part of our Actionable Data Insights series, brought to you by Kate Barrett (IDM Tutor/Founder eFocus Marketing) and Pure360 we show a detailed way in how to conduct a data audit, with a range of strategies, hints and tips that you can use within your own business.

Having an in-depth understanding of what data you have in your business, where it is, how it is used and why it’s collected is imperative to creating a solid email marketing strategy that WORKS!

Whether you’re in a marketing department doing it all for yourselves or are fortunate enough to have access to a specific data team and analysts who can dig through the wealth of information available to your business, as a marketer YOU need to have an insight into your current data situation so that you can use it to inform what you do now, and what you are able to do next, to advance your strategy.

You need to learn to love your data.

According to Salesforce’s 5th State of Marketing research, the median number of data sources used by marketing organisations is projected to jump from 10 in 2017 to 15 in 2019 — a 50% increase in just two years.  That’s a whole lot of data to get to grips with!

Data Sources

Until we have access in a meaningful format to the data we collect, collect the right data and have the capacity to disseminate it into a layout that we can actually use to identify different types of customers, where they are on their journey and what they need, we will struggle to further increase relevancy of our campaigns past a basic level.

So, let’s break it down and start to understand your current data situation…

Understand Your Data Pyramid

There are five main types of data in your data pyramid, each representing certain information you may be accumulating in your business.  As we move up the pyramid, the data becomes more and more valuable. Let’s start at the bottom…

AI

  1. Known Data

This is data that is collected directly from asking the subscriber, including details such as their preferences and…

Demographic data: who your buyer is; date of birth, address, name, education, interests and income etc.

Firmographic data: information used to categorise organisations; geographic area, number of clients, type of organisation, industry and size etc.

Be careful with known data – the reason it’s at the bottom of the pyramid is because it’s the information most of us have, but it is also the most unreliable in the long term and actually one of the most valuable in the short term.  Consider this… if you’re a home improvement company and when someone signs up you ask them if they’re planning on renovating their bathroom in the next 6 months and they answer yes. This is extremely valuable information that you may not otherwise have known about, or certainly wouldn’t have known a timeframe for. However, once that time frame has passed and/or they have completed their renovation, this data quickly becomes out of date and the emails that you’re sending recommending new bathroom suites based on this answer, soon become unwanted and most likely annoying to the consumer.

  1. Cultural Data

This is data which relates to differences in cultural norms and surrounds your wider information; such as connecting different products together (by category, by type, by relevancy, by upsell/cross-sell options for example), or knowing what type of products/services are most relevant to people in different areas of the country, or around the world.

For example, if you’re a supermarket, the products you advertise and which are attractive to people in Scotland, Wales or England will be slightly different depending on the specific region, tastes and trends.

Crossing over between known data and cultural data is Psychographic data. This refers to the ‘personality and emotions’ based on the behaviour of your subscriber and is linked to purchase choices including attitudes, lifestyle, hobbies, risk aversion, personality and leadership traits. magazines read and TV watched. It tells you more about ‘why’ your subscriber might be interacting or purchasing.

  1. Contextual Data

This includes information about what’s happening for the subscriber right now, such as where they are (geographically), what device they are using to open their email, the current weather conditions or the time of day.

Real-time content involves sections of your emails that are personalised at the moment a subscriber opens the email. This could include features such as:

  • countdown timers
  • weather forecasts/change imagery based on the weather
  • maps
  • polls
  • trackers (delivery)
  • live social media feeds

For example, if you are a retailer with multiple shops on the high street around the country, you may include a map in your content showing the location of the shop closest to the subscriber when they open the email. Using geo-targeting, this map would change, within the same email, if the subscriber then opened it again in a different part of the country, to show the nearest store to their current location.

  1. Behavioural Data

Tracking subscriber behaviour on your website using a dropped pixel and cookie tracking can give you a wealth of information about what your prospect needs RIGHT NOW: products they’ve browsed (categories, subcategories or individual products), blog posts they’ve read, videos they’ve watched and any other actions they’ve taken; telling you what they are actively looking for.

For example, if someone is browsing your FAQs, they are telling you with this behaviour that they are looking for more help. If they are looking at multiple products of the same type, they are trying to choose which is right for them. If they are browsing multiple categories, they may be looking for inspiration.

This can also be as simple as identifying the lead magnet they chose that incentivised the sign-up – for example, a first order discount amount, free download, webinar sign-up or gaining access to a free video series.

This alone will give you an abundance of information about what the customer is interested in – for example, the topic of the free download they chose, the format of information they prefer and where they are in their research. If they are signing up for a first order discount, for example, they may be closer to considering making a purchase from you and/or be more price sensitive.

All of this will inform how you can best serve them additional content to move them through the buying process.

  1. Purchase Data

This will include information such as what, when and how many times they’ve purchased from you previously.

This quantitative data will come from a variety of sources in your business (data you’ve collected, tracked and that which you have created through analysis). You’ll also have a range of qualitative data from sources such as focus groups, user experience studies, surveys, Net Promoter Score (NPS), customer service feedback and social media.

Example data

Table

By bringing these types of data together, you can identify markers that allow you to discover the type of prospect they are, what they need from you right now and how you can best help them to move forward.

This is most useful when you can create a Single Customer View – where all the data you hold about each of your customers is stored and consolidated into one single, easy to read record in your database.  This should also include data pulled from all other marketing channels, if possible.

A true single customer view means being able to use this huge amount of data in a meaningful way to create a fuller, personalised picture of the customer and their journey. By doing so, you will be able to improve future interactions with customers and provide a more targeted, cohesive experience through a greater insight into customers’ behaviours and interactions, and hopefully an omnichannel marketing strategy.

TASK:

Start by conducting a data audit, using our data audit cheatsheet to understand your current data landscape. Look at what data you have in your business currently (at each level of the data pyramid), where it is stored (who has access to it and how is it currently used), where the gaps are (how you access data to use in your email marketing and how you add to your current data set to enhance your customer picture) and how all this fits together to create a combined picture of each subscriber.

Within our next Actionable Data Insights Series guide we look at areas such as how to get your data house in order, how to collect more data as part of your sign-up process, progressive profiling, analysing your data, plus much more, so be sure to keep an eye out for it once it is launched.

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