Ask your peers: How to personalise at scale

We put marketers’ questions to our community in a new series of articles aiming to provide practical advice and connect business leaders. This week it is the turn of Sandra Moran, CMCXO at management software company Workforce:

“I am interested in how others are thinking about delivering more personalised experiences to buyers at scale. I’d love to know how they are increasing the use of information to deliver personalised experiences that will be meaningful to customers.”

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Personalisation has been a salient term in digital marketing for many a year and as the technological shackles continue to loosen for the majority of businesses, it is no surprise that the intelligent use of data represented a common response for delivering personalisation at scale.

Artificial intelligence (AI) is perhaps the best-known tech solution for optimising and personalising large datasets, and this technology too was frequently referenced alongside machine learning and automation.

Other personalisation suggestions surround the potential of gamification, the need for a single customer view and how ‘send all’ is a term all marketers need to ignore.

Jason Ball, founder of B2B marketing agency Considered Content: ‘Data is notoriously inaccurate.’

“While the theory of personalisation is great – to show we understand the customer better than our competitors – delivering it is incredibly challenging. The key problem is data. It is notoriously inaccurate. For all the claims of third-party data providers, one study by MIT and Melbourne Business School found that something as simple as gender targeting is accurate just 42.3% of the time.

“A better approach is to focus less on who customers are and more on what they need to get done. By using something like the Jobs To Be Done framework, we can create a limited number of content streams and use engagement metrics to track interest and relevance.”

Genefa Murphy, CMO at cloud company Five9: ‘Always consider AI and automation technologies.’

“Technology such as AI and automation are key in providing fluid experiences that enable consumers to move through the most efficient and personalised pathway across channels and between self-service and live agents, keeping context and creating a frictionless customer journey. Tapping into data from self-service and live customer interactions helps you better understand your customer and design journeys that meet – and even anticipate – their needs.”

Sam Martin-Ross, founder and MD of data-driven marketing agency Digital Uncut: ‘Paid ads are great for scaled personalisation.’

“With paid ads, we can deliver more personalised experiences at scale using dynamic audiences. These audiences can be based on website interaction and purchase behaviour. At a basic level, you can show old vs new customers different messaging for example. Shopify & email platforms like Klaviyo integrate directly with ad platforms such as Facebook, allowing you to upload your past customers and create audiences to target.”

Stuart Russell, chief strategy officer at Planning-inc, a leading first-party data agency: ‘You can get a single customer view through technology.’

“For many businesses, there needs to be investment in unifying customer data to create an operationalised single customer view. By joining together omnichannel behavioural and transactional data, predictive models built with machine learning will industrialise and automate insights that uncover correlations in data you couldn’t have otherwise leveraged. A robust unified view of the customer is the foundation upon which highly personalised customer experiences can be delivered, which are crucial to driving retention.”

Emma Clark, head of customer engagement strategy at media agency VCCP: ‘Think about gamification.’

“Winning brands are delivering personalised experiences to buyers at scale by effectively embracing gamification, using personal goals, alerts, nudges and rewards. Others are curating content, tailoring messaging, triggering comms, and even creating highly personalising product experiences such as Stitch Fix’s personal styling or personalised nutrition from Vitl.”

Felix Kruth, chief product officer at customer loyalty platform Voyado: ‘We are at the preference and intent personalisation stage.’

“When personalising at scale, we still want to design an experience that meets and exceeds every customer’s requirements. The approach most talked about on LinkedIn is preference and intent personalisation. This type of personalisation tries to create a better understanding by predicting what you, as a customer, are looking for. It can be done in two different ways, either by looking at historical preference or current intent. In a perfect world, you would start the customer interaction with a high degree of historical preference and switch to current intent as the interaction progresses.”

Mark Clydesdale, VP, corporate strategy & GTM at CXM company Merkle: ‘Invest in data analysts.’

“Customers expect brands to know who they are: What they like, dislike, what products and services they are interested in, when they like to shop and through which mediums.

“Data insights help businesses to understand what customers want and how they want it delivered at any given moment. To unlock this level of customer insight requires not only advanced analytics, but also investment in people with the deep analytical skills to drive value from the data to make meaningful business decisions. Machine learning, for example, cannot explain the reasoning behind people’s choices, nor can it apply common sense.”

Mike Ferguson, vice president client services, general manager EMEA, at data platform Redpoint Global: ‘Change [to] the golden record.’

“To accomplish personalisation at scale, brands can adopt a customer-centric view that combines all data into a single customer view, accessible to all applications and all business and marketing users. Also known as a golden record, this single view blends all identifying information about a customer with a full transactional trail.

“Using persistent keys, this record doubles as a single source of truth for the customer because the unified profile is updated in real time as a customer journey unfolds. It therefore provides brands with a contextual understanding of an individual customer that deepens over time. A brand becomes, in a sense, the corner shop owner that knows everything about each individual customer.”

Scott Ewings, chief experience officer business consultants TPXimpact: ‘AI is evolving but companies need to be selective.’

“As Artificial Intelligence models become ever more sophisticated, it will play an increasingly large role in the creation of personalised digital experiences. AI is already being used to analyse customers’ preferences and provide them with personalised product recommendations, to predict user needs and to deliver efficient customer service at scale.

“While AI provides many game-changing opportunities for marketers, it is important that practitioners do not let themselves be swept up in the excitement of new AI trends, but instead take time to consider how new technologies can add value to their organisation, and more importantly their customers.”

If you want to take part in our next Ask your peers article, submit your question now.