Maximising the value of customer data is the focus of new personalised marketing models, but significant organisational change is needed to extract that value.
Customer data is now everything, and an increasingly valuable part of businesses everywhere - it lies at the very heart of the new data driven marketing models being employed world over.
The new data driven marketing models enable a business to improve its customers' experiences of the business, thus ensuring those customers don't go elsewhere. Critically though, that data is also used to enable businesses to offer customers goods or services they didn’t know they wanted, but which the data indicates that they are likely to want, and so buy. This is highly valuable stuff.
The trouble is that accessing the value in customer data is not straightforward, involving new investment and organisational change.
Here’s what’s needed to make the new marketing models work.
- The data must be able to be used for marketing purposes (with all relevant permissions).
- It must be gathered up from all parts of the business (customer origination, customer care, purchasing, delivery, operations, sales channels) and pulled together to create an accurate and complete profile of the customer.
- From there, the business needs to be able to group customers appropriately, based on value creation potential, and then create personalised ‘next best action’ messages for each set of customers.
- Those messages then have to be delivered to the customer groups, through appropriate channels, and at the optimal point of each customer’s decision-making journey through the business.
- The final step is being able to track customers’ responses to the messaging, the conversion rates, and the value derived, with relevant business functions learning and adjusting accordingly, and the ensuing data fed back into the system.
This means wholesale operational change.
- The business needs to invest in the technology to enable the data collation and the necessary analysis – this is new technology investment (of people, money and implementation time) that may not be in the existing capex plan.
- There must be enough people skilled in data analysis – unless the business already has this capacity in house, which can be redeployed, this means new headcount.
- To get the data and marketing elements working together well requires a collaborative relationship between the IR and Marketing teams – such a relationship probably hasn’t existed before and so will require cultural change.
- The business needs the agility to respond quickly to new information derived from customers about the products or services being offered, and to make whatever changes are necessary to respond quickly to customer desires – either to prevent the customers from going elsewhere to get what they want, or to ensure the customers act on the next best action messaging that is delivered to them.
- The business needs to deal with the very real cyber-security issues that go along with holding large amounts of (valuable) customer data.
The really hard part is that all this needs to happen now, not in 3 or 5 years. Can an existing business make the necessary internal changes in time, or does it create an alliance with a technology focused start-up and then remodel itself from there?
The NZ business community is alive to these issues. PwC NZ recently released its 2017 NZ CEO Survey (www.pwc.co.nz/ceosurvey). The responses centred on, as one might expect, the direct and indirect consequences (felt and anticipated) of our technological revolution. Of those surveyed, and among other issues highlighted, 91% were concerned about cyber-attacks, 66% are worried about changing consumer preferences, 38% say that technology will completely reshape their industry in 5 years, 53% will increase headcount, 72% see growth coming from JVs or strategic alliances and 41% will collaborate with entrepreneurs and start-ups. The ways in which businesses now need to deal with data driven marketing models, and so maximise their customer value in, is perhaps part of why our CEOs feel the way they do.
To drive revenue growth and improve customer experience, technology has to enable more efficient data collection, foster cross-functional collaboration, and support test-and-learn agility. It needs, in short, to underpin a new Marketing Operating Model (MOM).