Nearly all marketeers believe that personalisation helps to advance customer relationships, providing consumers with the experiences they expect. Examples demonstrate a strong lift from personalisation efforts and, as a result, increase customer loyalty.
The use of data for personalisation in marketing seems straightforward and simple yet despite huge investments in Marketing Clouds, DMPs, Campaign Management and Data Warehouse systems, it has eluded us for years.
Creating a unified view of the customer has been a challenge for even the most advanced companies. One major reason for this is that existing solutions weren’t designed to hold the diverse data held in today’s cross-channel marketing operations.
The resulting explosion in marketing tech has arguably made the problem worse for the vast majority of companies trying to engage with their customers in this time of fragmentation of channels, increased number of datasets and significant focus on consumer privacy.
Arguably, unlocking the power of personalised marketing may need the following 4 keys:
Key 1. Development of Personalisation Skills
Importance of effectively hiring, training and developing the key competencies for effective personalisation and building a customised marketing strategy.
Key 2. Atomising Your Custom Content
Turning your custom content into atomized pieces and combining them to build and scale powerful personalised content and experiences that deliver results.
Key 3. Prioritise Your Data
There’s a fine line between ‘personalised’ and ‘creepy’. When marketers don’t use personal data accurately — either using too many data points or using data in a way that is perceived as too personal, the brand will lose. Knowing how to prioritise your customer data to deliver highly targeted marketing messages is key.
Key 4. Offering Tailored Help
Tailored help is an approach to messaging that provides valuable customer assistance while using a limited number of data dimensions. This allows companies to offer very purposeful help to their customers without violating their sense of privacy.
And underneath all the 4 keys lay the effective use of data to drive every customer interaction, inspiring loyalty by personalising customer experiences in new ways that keep them coming back for more.
This focus on the customer as an individual coincides with a resurgence in disruptive technologies like artificial intelligence (AI), natural language processing, and computer vision. All of these technologies are maturing — going from game–changing ideas to mainstream, foundational business tools.
That’s where the Enterprise Customer Data Platform (CDP) comes in. This sophisticated data – first platform allows marketing and product teams from any company to personalise and create relevant experiences for every customer, regardless of the data source — today’s Enterprise Customer Data Platform — and has the potential to grow revenue faster, connect internal teams across shared priorities and inspire customer loyalty.
Teams who use an Enterprise CDP find that they rely on fewer fragmented tools in the quest for data-driven personalisation that increases engagement, purchase and brand loyalty, and allows companies to better understand their customer as individuals; their desires, preferences, behaviours and intents.
Japanese cosmetics company Shiseido is a leader in skin and hair care, cosmetics and fragrance, and also in the adoption of a CDP. With all the data they were collecting from their loyalty app, their marketing team found that they couldn’t keep up with the pace of digital insights and they could only guess at the right offers and recommendations to deliver to program members.
Shiseido wanted to leverage its loyalty program to upsell to its most engaged segment of customers, boosting profitability. The company also collected data from a number of disparate systems, such as their website, their stores’ point of sale system (POS), and loyalty program system. Its internal data warehousing tools were too slow to extract, transform and load data to the dynamic online customer behaviour data that became the foundation of their loyalty program.
Using Treasure Data, they quickly and reliably consolidated all their first-party data from the sources above. Once the data was ingested, they were able to enrich it with third-party data from Data Management Platforms (DMP) to better understand the demographics of their buyers. With an accurate, real-time view of their customers’ behaviour and the ability to segment and target them, they could start to personalise offers and communicate one to one for better response.
This translated into contributions to Shiseido’s bottom line. They saw a 20% increase in in-store revenue per loyalty member after one year as well as an 11% increase in revenue.
We will be at Dmexco in Cologne next week from 10~11 September 2019 in Hall 7 Booth B030a. Hope to see you there!