In this data-rich world, marketers cannot ignore the power of information. Indeed, we can all agree that working on gut instinct alone is no recipe for consistent success.
However, this doesn’t mean that creativity is dead. For campaigns borne of data analysis, creative minds draw out the methods and means by which we compel our target audience to take action. Simultaneously, creative campaigns will use data as the spine to support endeavours, and to prove campaign ROI.
The combination of accessible data analysis tools and ever-richer data sets means that there’s never been a better time to get your teeth into the numbers. Whether it’s big data or small data, marketers have an unprecedented opportunity to understand more about their audience, and to target them with perfect content in a confirmed context.
To get a picture of how marketers can incorporate data better in our campaigns for 2017, I spoke to14 data experts, who each provided their snippet of advice for the forthcoming year.
I think there are two main areas in which data can help with creating better marketing campaigns. The most obvious one that is on most people’s minds when they think of data-driven marketing is personalisation. There are many ways to personalise. The frequency with which you contact your customers may make the difference between your marketing being perceived as being very helpful and very annoying and this optimal frequency may be different for different individuals. The time of day, day of week and even day of month on which you contact someone may have a huge impact.
I was particularly surprised by how much the day of the month has an impact with certain types of campaigns. Naturally, building a data-driven customer segmentation is a great way of understanding your customers better and if you can couple that with a recommendation engine then you can really start cooking.
The other area in which data could be immensely useful and which doesn’t get spoken about much is in assessing the return on marketing investment (ROMI). There is an excellent article by Accenture titledTurbulence for the CMO, which explains how Chief Marketing Officers are under greater and greater pressure to justify the actions they take and to much more precisely quantify the impact of what they do on the bottom line. There is actually a solution for this; attribution modelling.
At first glance, this sounds like a problem that should be fairly easy to solve since it is just a matter of tying together an uplift in revenue to the relevant marketing campaigns that were at play. However, the devil is in the detail. If a marketing campaign included email, SMS, radio and TV all at once, to which channels do you attribute a successful sale? And what if one marketing channel on its own would not have been effective but perhaps a certain combination of channels is what made the overall marketing campaign effective. Fortunately, data science accurately assesses all of this.
I think marketers can use data much better by leveraging powerful open-source tools such asTensorFlow. As an example, I recently built a model that could, with 80% accuracy, predict whether a customer was male or female based on their first name. By using tools and approaches such as this, marketers can become much more individually precise about the experiences their customers undergo.
As a high-growth start-up, our marketing has involved a lot of experimentation and a very iterative approach to campaign costs. Thankfully, we use the enterprise level of Hubspot to manage our CMS, website hosting and CRM. Therefore, we can track campaign performance very accurately from initial traffic source, pages visited, CTA clicks, emails collected (open rates and response rates from those emails), and ultimately downloads.
We can therefore very quickly understand what channels perform the best for us by linking the cost of the campaign to download, and then optimise accordingly.
