It’s time for digital transformation to decline and die
Why read this? : We look at the difference between what digital transformation should do, and what it actually does. Learn the real question which
Why read this? : We look at how you source and analyse digital data. Learn the different external and internal sources you can use. We also cover the key legal and security challenges involved in using digital data. Plus, we show how to create data user stories to help define your needs. Read this to get better insights out of your digital data.
How this guide raises your game :-
As per our digital business model guide, every time a customer interacts with your brand online, you get data. Data underpins all your digital activities. Digital media. Social media. Your website. All your e-Commerce activities. All these generate data.
You use that data in many ways. To better understand online customer behaviour, for example. It tells you what’s working with customers, and what isn’t. You use it to look for insights, set targets and measure performance.
Digital data shows you the reach and impact of your digital media. It shows you the engagement customers have with your website and social media content. And it helps you optimise your e-Commerce content and product pages to drive more online sales.
Digital data is a key part of digital marketing. This guide covers where you find it, and how you use it.
Digital data comes from many different sources.
There’s external sources, where the data is aggregated and covers broad customer segments. The insights are usually about generalised online behaviours.
Internal data sources are usually more specific. You can drill down to individual customers and specific interactions. You can aggregate these to create broad insights and / or more personalised customer experiences.
We’ll focus here on the free sources you can use to find digital data. However, there are also paid sources like Similar Web if the free sources don’t meet your needs.
Most of the big online players like Google, Facebook and Amazon make some digital data available for free. Sharing data encourages you to use their platform more often, especially for online advertising.
Google is the most generous and helpful with its sharing of digital data.
They’re a good place to start as you try to look for online trends and business opportunities.
Google Trends lets you track the popularity of search topics and keywords. You use these to generate ideas. For example, see our article on finding customer needs through search trends.
It’s a flexible tool which lets you analyse search data. You can filter by different countries and time frames, for example. It gives you the specific words people search on, and lets you compare those to other search terms.
(See our secondary research guide for more examples of how to use Google Trends for insights).
Google Ads Keyword Research tool is another useful digital data source. It lets you dig deeper into specific paid search volumes on keywords than you can with Google Trends.
You use these insights to drive your SEO and paid search in your digital media plan.
(See our secondary research guide for more how to use Google Ads Keyword Research for insights).
Facebook also gives you access to their digital data when you book advertising space with them.
You have to set up a Business Account to access their Audience Insights tool. Through that, you access their digital data about what’s happening on Facebook.
You can filter by country, age, gender and interests to learn more about your potential target audience.
In this example, we’ve taken the total population of Facebook users in Australia. We can see which brands in different types of categories ar most popular by likes.
But we could also drill down further and look at different age, gender and location summaries. We could see how active they were on Facebook, and which devices they use. (which would influence the type of content we’d create – e.g. more mobile friendly content). We could also look at the same data for Instagram as they’re both owned by Meta.
You use this digital data to find insights and generate ideas. For example, the content on the most popular sites tells you what customers like. Looking at what competitors do helps you work out their competitive strategy. And of course, you can use these digital data insights to make sure your digital media lands in the right way.
You’ll find similar insight tools on Business Accounts in other social media channels like Twitter, LinkedIn, Pinterest and You Tube. They generally do a similar job.
Sales data on online shopping channels is usually harder to source than search and media data.
You can usually only access sales data if you have a direct business account with the retailer such as being an Amazon merchant. (See our online retailers guide for more on this).
But there are other tools you can use to get insights about e-Commerce. For example, you can use the Search function on online retail sites to identify Best Sellers.
Here, we looked at the fitness category on Amazon, for example. We can see 4 of the top 10 bestsellers were fitness band products.
If our online store niche was about fitness, that would tell us we’d need fitness bands in our range.
The same “Best seller search” would also identify which competitor products are selling well. You can use that to help shape your competitive advantage.
We regularly look at bestsellers on our Print on Demand supplier sites Redbubble and Spreadshirt, for example. It helps us stay on top of design trends for our T-shirt shop.
External data helps you build a picture of the category and your target audience. But, it can only take you so far. You can only access what those sources give you. And the data’s shared. Anyone can access it.
For data unique to your brand and customers, you need internal sources. Setting these up gives you more control over the data you capture.
The main internal digital data sources are usually :-
One of the first jobs when setting up a website is to attach it to Google Analytics.
Google Analytics is an online tool which tracks what people do when they visit websites. It’s a vital tool to understand what works and what doesn’t with customers.
This understanding helps you set and track key digital objectives and measures.
Google Analytics is an aggregated data source. It doesn’t identify individual visitors. But it does show what visitors as a whole do on your site. So, you’re able to look at common patterns of behaviours.
For example, Google Analytics can tell you how many visitors come to your site. But not just that, it can tell you what time of day they came, down to the last minute. It can identify which cities or countries they were in and what type of device and browser they used.
When connected with the right media tagging set-up (see our digital media guide for more on tagging), Google Analytics shows you how people found your site. It tells you which adverts or media channels they clicked to land on your page, for example. As they spend time on the site, it can tell you how long they spend on each page, how much of each page they read, and what they interact with.
This mostly happens in real-time. It gives you clear insights into what customers are doing on your website. What’s working well, so you can push it harder. And what’s not working well, so you can fix it.
There’s 4 steps to setting up Google Analytics :-
Once set up, it continuously captures and stores data about your website visitors. It has multiple levels of data including real time and audience data. But to keep it simple, we recommend you focus on :-
These terms relate back to the digital goals in our digital business model RESTART guide. Acquisition relates to the Reach goal. Behaviour to the Engagement goal. And Conversion to the Sell goal.
Acquisition tells you how customers found their way to your website. Did they click through from your social or SEO activities, for example? Or via a link from another site?
You generate this data by placing “tags” in your digital advertising campaigns.
These are small pieces of code, which send a notification to Google Analytics when a specific action happens. For example, someone clicks on the advert.
You use this data to evaluate the impact of your advertising and your media choices. You work out what works and what doesn’t based on how customers interact (or don’t).
Clearly, you then do more of what works. And less of what doesn’t. It makes sure you optimise your digital media spend. You should check this data regularly. In some cases, that could be daily. In others, monthly is OK.
The Behaviour section on Google Analytics tells you what customers do on your site. There are some key metrics you should review regularly. These include bounce rate, pages / session and average session duration.
Bounce rate is the percentage of people who land on a page but then don’t interact with it. They ‘bounce’ off the page and off the site.
You want customers to interact. That’s a sign of engagement. For example, you use calls to action like click a link, view a video, download a file and so on. If lots of customers don’t interact with a page (i.e. it has a high bounce rate), it suggests something’s wrong with that page.
Bounce rates vary from site to site and from category to category. As a rule of thumb, a bounce rate of 60%+ is usually cause for concern. Anything under 30% is usually good. And 30%-60% is about the ‘norm’. You can make it better, but it’s not a disaster.
The pages / session metric is helpful if your site is designed to be an information guide. Or where you want people to read a wide range of content. The average session duration is similar. This data is often used to measure sites where the objective is to build customer relationships. (rather than being an overt “sales” driven site).
Both metrics help measure customer engagement. And they often correlate closely with future brand (sales) choice.
With online store sites however, the measures might show more of a problem. If your objective is more conversion (i.e. sales) driven, you want customers to find the right products quickly. You want it to be fast and easy for them to buy. High numbers in pages / session and session duration may show products are hard to find. Or that something’s wrong with the site navigation.
So, think about the context of your site when analysing these numbers. Again, you should check this digital data regularly. Use it to adjust your website activity accordingly.
The final section in Google Analytics is Conversion. Here you set up specific events or goals to track. i.e. specific actions customers do on your website, which you want to measure.
These can be as simple as recording a sale on your e-commerce site. But they could be more complex. For example, people who viewed a page or added the product to their cart, but then didn’t buy.
They don’t always have to be sales conversions. They could be any call to action. Reading a specific page. Spending a set amount of time on the site. Downloading a specific tool. Registering for email updates. These would all be examples of conversion goals.
These measures link back to your business and marketing objectives. So, obviously you should evaluate them regularly. And adjust your website and e-Commerce activity as needed.
Google Analytics is a great place to start with digital data. Larger businesses with more complex requirements often move to other providers (Adobe Analytics, for example). But for most other businesses, Google Analytics meets most of their website digital data needs.
Beyond Google Analytics, you can also capture specific one-to-one individual data through your website.
For example, through a CRM system if you have one.
We cover how CRM is set up and its role in our marketing technology guide. We also have a separate article on B2B CRM, as it’s particularly common when dealing with professional customers.
The data you capture via CRM has to be carefully managed. You have to think about how much data you’ll capture, both on individuals and across all your customers.
For example, something like a newsletter may only require capturing an email address. But you may also want to capture when the sign-up happened, so you could tie it back to a specific campaign.
And while an email address is helpful, adding more digital data to that email address usually leads to richer insights.
If you have your own e-Commerce store, you get data from customers who buy from you. By nature of the transaction, you capture more detail about that customer. Their name, their shipping and billing address and what and when they bought.
As per our e-commerce payments article, you usually use a 3rd party payment gateway to manage their credit card details. But nonetheless, there’ll still be a large amount of digital data you’ll have about the online shopper.
This CRM and e-Commerce data is valuable to build up more insight about customers, to help you create more loyalty.
It helps you offer more personalised and relevant experiences. But it also comes with challenges from a legal and IT point of view, in terms of how you manage this data.
When you set up your data plan and systems, it’s important to remember capturing people’s individual data has a number of legal obligations.
These obligations mean you must follow the guidelines when it comes to managing personal data. Failure to comply can result in financial penalties.
Your customer data has to be held securely and have a secure process for access, managing and use of the data.
The server where your data is stored has to be secure against hacking or intrusion. And you should control who in your business can access or use that data. Anyone with access, should be trained on what they can and can’t do with personal digital data.
You should also ensure you’ve procedures and policies to manage specific situations. Such as when a customer asks to see what digital data you hold on them. Or asks for that data to be deleted. And even, what happens in the worst case if a hacker manages to get hold of that data.
The legal obligations will vary by country, but they usually follow similar principles. For the purposes of this guide, we’ll use the key legal obligations for businesses based in Australia.
In Australia, the the Australian Privacy Act 1988 (Cth) (AU Privacy Act) governs how businesses and organisations collect, use, disclose, store and grant access to ‘personal information’. Most countries have their own version of this.
The AU Privacy Act defines ‘personal information’ as “…information or an opinion, whether true or not, and whether recorded in a material form or not, about an identified individual, or an individual who is reasonably identifiable”.
Also, if you intend to contact customers directly – especially sending out emails, you should consider the laws around unsolicited messages. In Australia, this is covered by the Spam Act 2003 (Cth) (Australia). In simple terms, it requires you to have ‘permission to contact’ people directly.
This is why when you sign up for emails and newsletters, you’re asked to tick a box accepting the terms and conditions. This ‘proves’ the company has permission to contact. There are provisos within the act which must be followed. Allowing easy unsubscribing, for example. There can be legal consequences if not followed.
If you’re new to email and outbound communications, check the laws and seek advice from experienced practitioners. In general, having permission to contact is key. If you don’t have permission, you shouldn’t contact the customer.
To make use of all this data, you need analytical skills to interpret it, and then be able to convert it into ideas and actions to go into your marketing plan.
This is how you get value back from the data. Making your actions relevant to customers based on data and insights helps you drive more sales.
One of the best ways to link data to actions is to use the concept of data user stories.
These help you identify what you want to track and measure. This help you get the right data and reports to evaluate your performance.
A user story is a tool used in Agile software development to describe a software feature from an end-user perspective. The user story describes the type of user, what they want and why. It helps create a simplified description of a requirement for whoever is building the solution for that need. It’s written as :-
As a (USER), I want to (NEED) so that I can (BENEFIT).
The format of the user story help you create a list of priorities for your digital data system set-up. It helps you identify which sources of data you need to capture the data. And it helps you define which measures you need, how they’ll be reported and how actions will come out of the data.
As a (digital marketer / e-commerce store owner), I want to (understand customer behaviours) so that I can (evaluate the impact of my digital activity).
Here, the data source is likely to be the website or e-Commerce platform. The measures will relate to activities intended to drive conversions or sales.
As a (business analyst), I want to (run regular performance reports to identify new segments) so that I can (generate ideas for future marketing activity).
In this example, the data sources will be external digital media, and the measures will relate to specific trend identification.
As a (customer service representative), I want to see the full history of a customer, so that I can (better tailor my response when they contact me).
And finally, in this example, the data source will be the CRM program or e-Commerce store. And the requirement is to set up quick and easy access for the customer service team to be able to manage and respond to enquiries.
It helps them track customer feedback and look for trends they can show the marketing team.
When you articulate your data needs with a user story like this, it helps you define how best to solve these goals.
You can sometimes manage this digital data user story in-house. Something simple like Google Analytics can be set-up and run by an individual business owner, for example.
But more sophisticated options require more expertise and bigger teams. The data user story approach helps engage IT teams, agencies and specialist partners when your requirements are more complex.
Once you have basic data flows working and you start to understand your data, there’s still much more you can do.
For example, Gartner published a data maturity model a few years ago. It showed the more data mature you are, the better the quality of data, analysis and insight you carry out. It claimed there’s 4 levels of data maturity :-
Most businesses operate at the descriptive level. They focus on what has happened in the past. This is the base level of maturity. You understand the history of how customers interacted with you online. A descriptive analysis might say for example, that there was a spike in your online sales last month.
With better analytical skills, you move from what happened to why it happened. This diagnosis of a change in behaviour helps you attribute outcomes from previous actions. It can be used to set your future direction. For example, you might attribute that spike in online sales to a sales promotion or advertising campaign.
However, diagnosis isn’t always easy. It helps to know basic statistical techniques to look for patterns and richer insights. For example, you can look for correlations and do regression analysis to be more predictive. So, if we ran the same sales promotion next month, this would give us a more accurate forecast, based on what happened before.
The highest level of digital data maturity is where you get prescriptive. This is an area where marketing technology systems like AI and machine learning are taking over from human analysis. Computer systems can analyse large volumes of data in real-time and make more accurate predictions. They can be automated to recommend specific actions without having to ask specific questions. This level of maturity usually requires the services of a data scientist and specialist software and statistical techniques.
This guide has shown the opportunities offered by learning how to source and use digital data. The key is to identify insights which you can turn into better customer experiences, and drive more sales. It means your marketing decisions are based more on factual data and less on gut instinct.
That’s not to say digital data is infallible, and that gut instinct should be ignored. Remember, the data you capture is based on individual customers. And the only thing that’s predictable about individual customers is that they’re unpredictable. But you can use digital data to help reduce some of that unpredictability.
We’ve lots of experience in sourcing and using digital data. Our coaching and consulting services can help you build your skills, and help you find better digital insights.
Get in touch to learn more about how we can help you use your digital data to grow your business.
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