Why You Should Be Unhappy With Your Marketing…even if you are not!

Pharmaceutical marketers seem to be rapidly losing the ability to understand and influence their customers. For many years, Pharmaceutical marketers were blindsided by their own successes and relied too strongly on innovative new products.


 

Several studies reveal that the majority of CEOs believe that the number one driver of revenue growth is new products. This could be the case in the Pharmaceutical industry also with the constant M&A activity to acquire pipeline. In addition, line extensions were also quite a common phenomenon in the Pharmaceutical industry as a quick fix to gaining a ‘new product’. Nielsen BASES reported that 93% of all new consumer products fail within the first 3 years, and product databases show that line extensions are actually more likely to fail than legitimate new products. It has been seen many times that no matter how loved the parent product, this does not automatically transfer into the line extension. The marketers tend not to attract new users which, in turn, mean that the users they attract cannibalize the original product. I can think of many Pharmaceutical brand cases where this has happened.

 

Some Pharmaceutical marketing teams have realized that, as costs rise and differentiation becomes less and less between products, Pharmaceutical sales and marketing efficiency must grow. The key to this is a thorough understanding of customers’ needs and drivers, even more than the customers themselves understand them.

It Is Not ‘Business As Usual’ anymore.

 

To win in this environment, Pharmaceutical marketers need a stronger understanding of their customers than ever before; they also need to understand what their customers’ need that will drive their behavior, and how to market to these needs more efficiently and effectively than ever before. Pharmaceutical marketing is certainly not dead but it is undergoing unprecedented changes that are not within the typical realms of many Pharmaceutical companies’ expectations. It is not ‘business as usual’ anymore. Marketing success has become a key driver of shareholder value, and is more important than ever. But how do you achieve marketing success? In a Forbes article by Jack Trout, a survey of top executives was cited in which they were asked their business priorities in order, and the results in order were: finance, sales, production, management, legal and people. Mr. Trout noted that missing from that list were the two basics that Peter F. Drucker had cited in 1973 i.e. marketing and innovation.

 

Marketing is important but it is slipping down the priority list of CEOs. The fault is not, however, with CEOs but with marketers as many have let their brands become commodities rather than highly differentiated brands due to poor marketing. What I mean by ‘brands become commodities’ is wherein the brand (or company services or products) is very similar to its competitors and almost interchangeable.

 

 

A study (by Copernicus Greenfield) interestingly examined the extent of brand commoditization. In this study, an alarming thing I noted was that Pharmaceutical brands included were seen as highly commoditized compared with brands like Dunkin’ Donuts/Starbucks. The Pharmaceutical industry marketers are doing a far worse job at differentiating their brands than coffee shops! This is entirely preventable with strong marketing.

 

When brands are highly commoditized, and the perceived product differences no longer exist – or are small – then price becomes an important factor. When you understand this, you can see how generics can come straight in and claim a large share of the market. In fact, in Pharmaceutical markets that have become highly commoditized, where the product itself has little intrinsic value (e.g. G-CSF and the epoietins), the biosimilars were able to have highly successful uptake. On the other hand, in other categories where the product value proposition was seen as higher (e.g. somatropin) and more highly differentiated, the biosimilars were not able to achieve the same level of success.

 

One often sees lazy Pharmaceutical marketing where the marketers find an easy differentiator (e.g. ‘mode of action’) and base all their marketing on that easy, obvious differentiator. This may be successful, but only if the marketers have securely tied that differentiator to a strong driver – such as efficacy; if not, the results hoped for will not be forthcoming.

 

Let’s consider a non-Pharmaceutical example i.e. washing powder. You want it to be effective in washing your laundry and making your whites whiter than white. Your mode of action may be different. Smelling nice may be an added benefit. However, if you market it only on your mode of action or smelling nice, your customers may think it is not particularly good at washing. You would be better off starting with the ‘whiter than white wash’ message and adding ‘mode of action’ and ‘nice smell’ as secondary messages.

 

 

I have a Pharmaceutical example of a brand we worked with. The brand had great clinical data on efficacy, a minimal side effect profile as well as a strong safety profile. However, this brand was just failing to thrive; two years post launch and it was still battling with a single digit market share and not growing. When we examined the data we noticed that it didn’t look like a particularly effective drug, so we were thinking it would have to be positioned for mild cases of the condition. However, when we looked into this further, we found that it was a highly effective drug and the marketing team had neglected to even discuss efficacy as a message as they felt the fact it was launched and approved meant it was highly effective. They had decided to focus on what I would consider secondary messages, such as ‘lack of weight gain’, and completely neglected efficacy, which was the number one driver message! By changing their messaging to analytics-identified drivers, they were able to double their market share in 6 months with the same budget, something they had not been able to achieve in the preceding years. It is so important to really get to grips with the data and base your marketing on that.

It is clear that marketers must be able to understand how to deal with the challenges faced, measure and justify their activities to deal with these challenges, respond appropriately, and also be able to prove that these activities are leading to increased bottom line growth for the company. Pharmaceutical marketers need to demonstrate that they are spending wisely but often lack the information to make well informed decisions. Much of the time, instead of linking an activity to a financial result, marketers become too busy showing brand awareness and tracking survey results. They do not tie these to actual revenue figures very successfully which, of course, leads to distrust with the Board.

 

Sales and marketing are one of biggest – if not THE biggest – investments in a Pharma company and yet it’s a sad fact that many marketers could not argue strongly which components of their marketing are leading to what financial results. The industry is seriously behind in these measures and still rely on poor metrics, anecdotes, gut feel, basic ROI as well as competitor size, spend and actions to guide decisions in these areas. It is time to regain control and, with it, credibility. This is where using sophisticated analytics will stop spend on knee-jerk systems and campaigns that are a reaction to competitors, and help concentrate on the real role of the marketing department: to know and understand the customer, and translate this profitably to the product and business strategy.

 

 

The key to tying marketing to revenue and profit results successfully is not an art or science but mathematics and code…. more precisely, strong current data-driven analytics and strong personalized context marketing or ‘micromoment marketing’ using AI. This is essentially personalizing every individual’s digital journey based on using AI to analyze others like them, and their own online behaviour in order to serve up the right content, in the right channel, in the right sequence, at the right time. We have created a system like this for a company and the results were outstanding in terms of revenue and profit gain. Of course, our custom built one is not the only one out there and this is now becoming a lot more common than many realize.

 

There is a lot of hype about AI so it is understandable that Pharmaceutical executives may be skeptical. However, when correctly used, companies can transform their results through a thorough understanding of their individual customers, their products and competitors’ drivers, and know exactly what they need to serve up (via the algorithms) – and spend – to create a specific financial result. Still, there are precautions.

 

Firstly, the system must be designed to analyze the right data and deliver up the right omni-channel experience.

 

And not just any data… garbage in, garbage out. The data must be planned and processed in a way that works reliably with the algorithms and must reflect the market in which the data will be used.

 

AI is all about making better decisions, quicker; making decisions that are not driven by the same data that everyone else is buying into but completely tailored to each individual customers needs. When a company uses AI to gain a thorough and deep understanding of its customers and the different customer segments – and how they perceive value in the drugs on offer – and use that knowledge to examine all aspects of their marketing hindering their growth, and then using AI to deliver a stronger personalized customer experience,  revenue growth and profit result and the company is in a far better position to grow profitably in a downturn economy.

 

Analytics using past performance data may be interesting, but can’t answer questions such as: What is happening now? What will happen in the near future and how can I impact that by making resource, allocation or focus changes? The prominence moves from measurement to understanding. AI techniques, based on real and current  big data, along with modeling and prediction, allow us to develop insight into what is happening in our world and then translate that insight into personalized automated action with reliable accuracy of results.