It’s relatively easy for businesses to start communicating with customers via mobile messaging.
All you need are your customers’ phone numbers and an intelligent mobile messaging system linked to your customer ops tech stack.
Then you can start automating processes and communications. For example:
– If you’re a retailer, you can ensure a parcel leaving a delivery depot triggers a notification message
– If you’re a bank, you can automatically send a message asking a customer to get in touch when a card is declined
– If you’re a health insurer, you can send reminder messages to patients when it’s time to take their medication
(To check out the many messaging use cases out there, read our SMS and RCS use case guide.)
Using data insights to personalize mobile messages
But to maximize the potential of what is fast becoming the most important business-customer communications channel, you need data insights.
More specifically, you need to:
– Learn about the individual and the situation they’re in – then anticipate what you can do for them in precise moments.
– Monitor and evaluate messaging data – such as message volumes and success rates
But here’s the thing. A research study recently commissioned by OpenMarket shows that businesses find it hard to get the data processes and insights they need in place.
Data insights research findings
Our research into the impact of AI on CX gathered insights from 4,000 consumers and 600 CX leaders that work for large brands.
The CX leaders say some of their biggest challenges in designing and delivering efficient and empathetic interactions include:
– Leveraging data and insights to optimize interactions (79%)
– Integrating with existing systems and processes (81%)
– Silos and lack of data sharing across the business (77%)
We also have anecdotal evidence to back up these findings. Our business mobile messaging consulting teams speak to brands on a daily basis – many of them huge global enterprises. Time after time these brands speak of fears that they lack the expertise, resources or processes to use data to make a difference to their mobile messaging.
But as soon as they receive accessible reports and clever visualizations of mobile messaging insights, they realize they can identify trends and patterns at a glance.
The right mobile messaging platform
None of this needs to be complicated.
A good mobile messaging platform should help you bring your own data together with third-party information – such as demographic details or data from marketing plug-ins.
Every interaction should ultimately become useful data too. This can be fed back to inform and improve future interactions.
A platform that helps you extract maximum value from data should make personalizing your customer experiences a joy – even for data novices. You should be able to watch, learn, test and optimize.
But let’s be realistic. Human help needs to be a key part of the messaging data puzzle. Look out for messaging providers that deliver consultation as part of the package.
Want to find out more about putting a multi-channel, AI-powered, data-ready messaging program in place?
Read our Empathy in the Age of AI strategy guide.