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Targeting individual customers is the holy grail of personalization. Automation is the means to get there.

By Adam Chapman on Dec 4, 2018

In days of yore, marketing was a much more manual and much less precise exercise. Companies relied on gathering information from broad customer segments to mount their campaigns. The one-size-fits-all approach aligned well with the ‘build it and they will come’ ethos of the day; the unshaken belief that product ate personal preference for breakfast.    

Fortunately, technological innovations and a competitive marketplace have put an end to that complacency, with customer-centricity and personalization tools becoming the gold standard.  

Companies now launch far more targeted campaigns, but when it comes to the holy grail of personalization – targeting individual customers – there is a growing consensus that marketing automation will be the means to get there.     

Marketing automation, whose ultimate goal is to use artificial intelligence to design customer journeys, to systematically gather insights along the way and to constantly learn from and action these insights, is a level of sophistication we associate with Amazon.

But where do pharma companies sit in this cycle of maturity?

Pharma companies are at the stage of gathering data and deepening their understanding of their customers, says Philippe Kirby, Digital Capabilities & Analytics Director, MSD International. This is the prerequisite to deploying marketing automation tools, he adds.

He likens it to a crawl-walk-run approach.“Using analytics to capture really good insights on my customers would be the crawl. Utilizing customer insights to develop personalization strategies, that would be the walk and then the run would be to automate marketing campaigns.”

Much of the focus has been on understanding channel interactions over the last few years but analyzing content consumption (i.e. what content target audiences are really reading or downloading) is where the industry stands to learn a lot more, he says. This will unlock far more valuable insights into customer behaviour and facilitate more tailored tactics.  

Progress is certainly afoot, however. Companies are increasingly using tools such as Google analytics, tagging tools and DMPs (Data Management Platforms), and working with social media groups such as Facebook and LinkedIn to engage customers, says Kirby. This will enable companies to do more sophisticated segmentation approaches, leveraging external customer data sets.

Fruitful partnership  
To advance its automation efforts, MSD has an ongoing partnership with software company Aktana. Piggybacking on Veeva’s database, Aktana functions as a suggestion engine that offers MSD tailored suggestions based on static information it has on brand strategy and customer data and dynamic, historical data gathered with each customer interaction.

“You have to start with base information you have on your customers and then you have to complement that with brand objectives and then iterate. With each customer interaction the suggestion engine learns and starts to help you achieve your brand & customer objectives’” says Kirby. 

The suggestion engine will provide recommendations but in the end it is always the rep who decides on the interaction and content. For example. An MSD rep will get a recommendation to send an email with content A but may send instead send an email with content B. The suggestion engine will learn from that too.  

In the classical model of trigger-based marketing — where you identify key events in the customer journey and respond to them — this is where it might end. But marketing automation tools are constantly learning. The suggestion engine will have logged the history of this interaction and provides marketers with ever-more refined content and channel suggestions.

This kind of methodology is also a boon for A-B testing, where you send similar versions of an e-mail to a subsegment of customers, changing one element, such as the subject line. Machine learning will very quickly tell which email subject is working best.

Marketing automation tools can speed up these agile processes, says Kirby. It has also yielded some successful results, although is limited in scope. “The only problem with the suggestion engine approach right now is it's still very rep-centric. It's more focused on the field force. The next step is to work out how we go beyond that to cover end-to-end marketing campaigns to help us better engage our customers.”

Assessing automation
To gauge whether these efforts are bearing fruits, MSD uses an engagement score based on frequency, recency and time spent as key measures, says Kirby. Each channel is scored on these measures and then aggregated to provide an overall customer engagement score on a scale of one to ten.

These insights must prompt you to start pursuing more iterative and agile processes faster, says Kirby.

“You need to be able to learn and try shorter cycles rather than doing brand planning with maybe two or three resets during a year. We’re now doing at least a monthly cycle to adjust our campaigns based on customer insights.”

At the end of the cycle, the AI feedback can advise what machine learning tactics to adopt in the next cycle or campaign, he adds.

You must adapt your processes, Kirby stresses. If you are not working on shorter iterations and actioning insights, it is a waste of time and resources.

Digital immaturity
If you think simply throwing marketing automation tools into the mix will provide you with ready-made solutions, you are sorely mistaken, says Kirby. He speaks from experience.   

“An affiliate came in and said, 'I want a marketing automation tool', so you have to ask them some key questions, ‘Do you have your analytics set up? Do you understand your customers? Do you have profiles you can mine? Have you thought through your content strategies and do you understand what content works, what content doesn't? Do you have a digital reach > 50 % (consents)?’ Until you get that right, you're not going to do marketing automation.”

The overall digital maturity and nature of the market will also play a key role. Access to physicians, which differs from country to country, will impact how you can measure what’s going on with your customers, says Kirby. 

On paper, the world of digital is critical in countries where face to face interactions are limited, but there is another factor to consider; how open the market is to digital, he says. MSD have encountered a resistance to digital in Japan, for instance, where it is a symbol of status for physicians to be visited by reps. This will of course change over time as new generations of HCPs come into the market and we’ll need to be ready for that.

The success of marketing automation will depend largely on the mindset and skillset of the marketer, says Kirby. “One of the hurdles we encountered when we went to some markets was that our marketers were not ready for this yet. We need to do a lot more awareness, training and change management in general.”