Marketers have access to more information about their customers than ever before, but generating usable insights from those mountains of data and launching campaigns quickly remains a major challenge.
Why? Many organisations still struggle to bridge the gap between their customer insights – audience data, market research and intelligence — and marketing execution, which is look-alike modelling, targeting and advertising.
Audience data often becomes muddied as it’s passed between key marketing stakeholders, data scientists and outside media agencies. Disparate spreadsheets, data sets and systems make it hard for media buyers to operate based on the most recent, relevant audience data stream.
The key is to harness the power of big data while removing the roadblocks that keep audience insights siloed across the organisation.
Only then can marketers target the right audience with the right message in the right place, in order to maximise their data for greater ROI.
How to eliminate the phone data game
1. Move beyond personas
The belief that a company has four buyer personas is a great place to start, but more customer data might reveal that the company in fact has 50, 100, or even more segments of customers.
Personas are a useful jumping off point to start conversations, but they should never replace in-depth audience data and micro-segmentation when it comes to strategic decision-making and ad buying.
2. Make data available to the entire team
Prioritise making real-time audience data available across the organisation—and to your third party media buyers. Empower marketers, audience researchers, data scientists and agencies to access the raw data they need to find correlations, segment more accurately and run real-time campaigns based on the freshest data.
While everybody likes the idea of fresher data, newer isn’t always necessarily better
Not sure how to centralise your data systems? One option is to ask your data partners if they can integrate for you. They often have a vested interest in integrating with as many platforms as possible, as this adds lasting value to their product.
“When we go to a client, we’re usually asking them to let us handle the integrations,” Peter Kang, co-founder of Barrel says about the companies he works with.
“The responsibility of the client is to either select software and tech that does integrate, or to apply the necessary pressure to their existing software providers to build those integrations.”
3. Ensure your data is accurate
If your marketing team is making data-driven decisions, the quality of their work depends on the quality of your audience data.
Stitching together the complete picture of your audience from multiple data sources is challenging, and integrating third-party data requires technical skill, expertise and careful consideration. You must heavily vet the data you buy for validity, consistency, and ease of integration with existing first-party data sets.
And for those not sure how to vet the quality of third-party data, here’s three quick questions to ask:
1. Are they transparent about data sourcing and uniqueness?
When considering any new data provider, the two first questions you should ask are:
Where is this data from?
How is it different from other data partners?
2. How much of their data is modelled Vs observed and how does that reflect on buyer intent?
When purchasing data, it’s important to evaluate whether you’d like to target people who are at the tipping point of a purchase (observed audience), or consumers higher up the funnel who may be likely to have future intent (modelled audience).
3. How recent is their data?
While everybody likes the idea of fresher data, newer isn’t always necessarily better. In some cases offline data, such as CRM or past purchase data, is brought back online and leveraged to target customers again.
In cases where you are trying to target audiences who are in a prime pre-purchase phase, real-time data is much more critical and can be the cornerstone to hitting leads at the right place and time.