According to Salesforce’s State Of Marketing 2016 report, 80% of marketers say that email is the core of their business. In other words, email is still the most used channel to get leads and then convert them into customers.
However, this doesn’t mean that email marketing has remained the same as it was 10 or even three years ago. In fact, a lot has changed and, perhaps the most notable difference is the emergence of what we call intelligent email marketing.
Intelligent email marketing uses data science and predictive intelligence to personalise the content that is emailed to your leads and customers.
The average office person receives 121 emails per day . The modern consumer is flooded with newsletters, promotions and invitations and the harsh truth is that 90% of these emails go to trash without even being opened.
To stand out from the crowd, marketers need to make sure the emails they’re sending to leads and customers are highly relevant to them at that time. Content and timing are key to your email marketing success. To appeal to your leads and customers directly and solve their real problems, personalisation is mandatory.
It is no longer enough to only know the name of the email recipient. You need to go further, real personalisation means that you know exactly where, in the buyer journey, they are and that you tailor your content and your offer to match.
Sounds tricky? It’s really not – this is where the intelligence part comes into play.
We’ve talked previously about big data analytics and how it’s producing huge volumes of data to extract relevant information about prospective and existing customers. In fact, Hubspot reports that 51% of marketers say enriching contact data quality is their most significant barrier to achieving email marketing success.
Data can revolutionise your email campaigns: data science can help you infer consumer behavior based on their preferred medium, preferred time to be online and their previous choices.
Let’s say you’re selling office supplies; based on the average timeframe between purchases, preferences for a certain type of paper and size of the company along with other factors, data science can help you know exactly when your customers may run out of paper – even before they do. This way, you can swoop in at the right time and send an email that says “Hey, don’t wait until you run out of paper.”
Much like its cousin, data science, predictive analysis uses data from numerous sources to anticipate customers’ needs. CRM data, browsing habits, web page views, downloads and click through rates are all examples of people’s actions that can be used to predict who they are, where they are in the buying process and what information they would find helpful.
A Forbes Insights survey showed that 86% of companies who used predictive intelligence had an increased ROI.
Here’s an example: let’s say your customer just purchased a new phone. Predictive intelligence can step in with recommendations for a phone case and other phone accessories that you could sell to them. However, these are not any recommendations; they are compatible with the phone model the customer purchased, match their colour preferences and are also based on purchases made by similar customers.
If you’re interested to learn more about Predictive Intelligence and how it can benefit small business both B2B and B2C here’s a couple of articles you may find interesting: