Marketing, sales and customer service are becoming blurred as customers navigate digitised journeys and expect consistency and reponsiveness across all touchpoints. This requires marketing agility, at scale.
Agility requires data, action and revision
Agile, in a marketing context, means using data and analytics to continuously source promising opportunities or solutions to problems in real time, deploying options quickly, evaluating the results, and rapidly iterating. At scale requires a large part of this to be automated.
The bottom line is to be able to deliver personalisation at scale. McKinsey says that you’ll be amply rewarded if you do, with uplifts in revenue of 5% to 15% and increases in marketing efficiency of 15% to 30% and reduction in acquisition costs by up to 50%.
This type of personalisation is the ultimate in “customer-first” because it is not just about the culture of the business or static knowledge of a customer. This is about dynamically knowing what a customer has just done and acting with the most likely engagement which will produce the desired outcome.
Four steps to personalisation at scale
How can this be done? McKinsey identifies four steps that lead to personalisation at scale:
- Mapping the customer journey for each customer segment. This means creating a group of behavioural-based customer segments, say 8 to 10, and then mapping a series of customer journeys for each segment. This will require the integration of data related to steps of the customer journey’s e.g. website, EDM, in-store, marketing.
- Planning how to respond to signals from the customers as they move through their customer journeys. That is, given that a signal is available e.g. a past buyer abandoning a current shopping cart, then a trigger message is sent via the most effective channel. This capability is about planning those trigger messages.
- Bringing together a cross-functional team of carefully selected people, including a campaign manager and staff from creative, digital media, analytics, operations, and IT. With the multiple skills in the room, and with sponsorship from the top, these types of teams are the most crucial personalisation asset.
- Having an agile cross-functional operational capabiity to respond to signals with trigger messages. This requires having sufficient data analytics and the right kind of marketing technology infrastructure in place. This is not about automated technology spitting out millions of similar messages but it’s about reacting to signals with personalised trigger messages. Even today it is unlikley that one platform can serve this whole function, so a marketing technology architecture is required.
The technology component needs to be assembled from across the ecommerce systems, CRM, data analytics, marketing automation and social engagement & listening. The team needs to have dashboards which capture, aggregate, and manage data from disparate systems; make decisions based on advanced propensity and next-best-action models; automate the delivery of campaigns and messages across channels; and feed customer tracking and message performance back into the system.
The right people working in the right agile way
That’s a tall order and it needs to be taken one step at a time in terms of addressing audience segments. Today, the technology assets would potentially include 3 main components – a platform for ecommerce, marketing automation, and CRM, another for data analytics, and another for social engagement and listening e.g. Sprinklr.
Integrating the technology is no simple matter, but getting the right team working together in the right agile way is the biggest challenge, and then that can be scaled up enabled by the technology. Starting with small bites of the audience segments is the way to get started.
When operating well and tracking the customer journey and responding to signals with relevant triggers the lines between marketing, sales and customer service will blur into one stream of data.