Create, test and iterate: Three steps to customer retention
When software brand Typeform sought to boost loyalty and retention, it turned to machine learning and personalisation to persuade customers to adopt new services.
The key to retaining customers is to personalise communications and make recommendations so relevant they drive up loyalty levels. Few would argue with that. The question is, how?
B2B software brand Typeform and growth marketing agency Iterable offered some answers in a case study presented at the Festival of Marketing. Iterable set out to boost Typeform’s customer retention and loyalty through personalised email content that showcases the service’s additional capabilities. As Nicoletta Ventura, lifecycle marketing strategist at Typeform, explained, this is important because customer success is heavily influenced by introducing clients to additional levels of integration.
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watch ‘How Typeform used personalisation to increase customer adoption by 25%’ at the Festival of Marketing on demand
Find out more about how brands can achieve growth through machine learning and personalisation. Watch Iterable’s session, ‘How Typeform used personalisation to increase customer adoption by 25%’, at the Festival of Marketing on demand now.
These tools allow Typeform’s clients to have more meaningful conversations with their customers and so generate more leads, Ventura explained. Good examples include incorporating customer feedback into Google Sheets as well as deploying analytics tools and the ability to feed insights from customer interactions into marketing automation software.
She revealed the current year has been
spent developing ways for the lifecycle marketing team at Typeform to flag up the most appropriate integration opportunities with each customer so they take a deeper dive into the available option.
Typeform and Iterable used machine learning to better understand which integrations were proving popular for customers within highly defined segments. This helped to inform which additional services similar customers would most likely be willing to try out. These were flagged up to them in a personalised email marketing campaign.
The campaign reached 90% of the company’s customer base, which was split into two groups. Half received the old ‘static’ email messages, in which messaging was not personalised. The other half received ‘dynamic’ content, which prioritised the features identified by machine learning as likely being of most interest to the recipient.
The result were impressive. Typeform saw a 25% increase in customer adoption among those receiving the dynamic, personalised messaging. They were also 11% more likely to try a new integration and overall the campaign led to a 5% rise in customer retention levels.
Dedicated to learning
When asked what the lessons of the campaign with Iterable were, Ventura was very clear on the four reasons she believes it was a success. “First of all, the mantra of create, test and iterate for me is key in marketing, but especially in lifecyle,” she said. “We need to think outside the box but at the same time we need to focus on results, we need to be data driven.
“The second [takeaway] is personalisation… we need to personalise, we need to deliver relevant content that adds value for our customers. Always use control groups to test your new strategies against the old ones, it’s the only way we have to measure the impact our strategies have.
“Finally, we need to break the silos. This campaign was a joint effort: we worked with the machine learning team, analytics team, marketing and customer success, it was great to see how we were working together, so we won together.” She also emphasised the need for constant improvement. Ventura made clear the team was not looking at the campaign with a feeling of ‘job done’.
Instead, the campaign data gleaned so far is being seen as a basis for confirming the principle that, if the right integration offer is promoted in personalised communications, customers will be more willing to try out the suggested feature. When they do, they are more likely to adopt the new capability and remain loyal.
So, the task now is to work on the lessons from campaigns run so far. Through this, Typefrom can refine the machine learning process, so it gets even better at suggesting which feature will capture the attention of each user and potentially boosts retention as they become more loyal. ■