How much do you understand about your online and offline data? Do you know what defines the two, or how to combine, monitor and measure each to gain a clear data picture?
Most marketers understand the strategic role that data plays – yet lack a combined, clearly defined strategy for it. But in practice, having a strategy that cuts across all online and offline channels and campaigns is crucial. It’s core to not only reach more people, but to tie campaigns back to common goals, and identify opportunities.
So what key things do you need to understand about your online and offline data to develop a clear and effective data strategy?
Asking Key Data Questions
“What is meant by online and offline data?”
Starting with the basics – what’s the difference between what’s termed as ‘online data’ or ‘offline data’?
- Offline data
Essentially, offline data can be described as data used for data-driven marketing, that has been collected from an offline source. Typically this data is stored in applications like your CRM and is often personally identifiable data (PII) (unless sourced from a third-party vendor). Contact information, purchase histories, loyalty card data, demographic data and more, may be examples of offline data. - Online data
Online data is data collected from online campaigns and platforms, such as social channels and email, plus any relevant data collected from website clickstreams.
“Should I link my online and offline data”
Linking online and offline data provides more value and insight across all of your data; by combining the two you’re closing the loop between what happens in your digital campaigns and offline transactions.
For example;
- If you onboard your first-party data, you’ll be able to use it to match that offline to what was previously anonymous online behaviour.
- For attribution and measurement that’s huge; you’ll be able to see if the campaigns you ran led to actual sales, even if those sales occurred offline.
“How can I do measurement and attribution if I’m targeting people through channels I don’t own?”
This is where compliant intermediaries come in – they can help by anonymising interaction data from the channels you want, meaning you can access the attribution, transaction and measurement data you need. This gives you a privacy-compliant way to tie your data to real people, and measure the true impact of your campaigns.
“Can I tie my digital campaign results back to my CRM data?”
It’s possible to tie this data together, so long as you have an intermediary who can anonymise the data. It’s not possible (or compliant) to see exactly who interacted with your campaigns via digital platforms, but with a privacy-safe link between you and the consumer (identity resolution) you can access the results you need.
“How can I use my customer data to find more people, similar to my best customers?”
Lookalike modelling is designed to help you find audiences who closely resemble your good-fit current customers. If you have a good level of accurate (quality) first-party data, you can use a third-party company to identify and define relevant prospects. Remember here that quality must be a priority as well as reach – don’t just focus on reach at any cost.
“Does my campaign plan match reality?”
Think about the audience you focus on when planning your campaigns – does that audience match the audience you end up targeting?
To keep your plans realistic, onboard your CRM data and use an intermediary to connect that insight to your channels in a privacy-safe way. This will mean your existing customer data can be used to inform online campaign targeting, closing the persona/action gap and ensuring cross-channel accuracy.
Ask the Right Questions To Define the Right Strategy
Consideration, testing, measurement, refinement, improvement – and questioning – are all required to define a complete, cohesive data strategy that combines all channels and campaigns for a clear view.
Of course, there are many more questions to ask than we’ve just outlined – you can access our full list of infrequently asked questions about data here, to start improving your own data marketing strategies.
