Where Pharma Digital Marketers Are Failing
Four Core Areas Where Pharma Digital Strategy Teams Could Improve Their Performance:
1. Think through the optimal data digital teams should be accessing in order to provide the sales and marketing teams, and the commercial teams. What do they need to know to achieve maximum customer engagement, revenue and profit? We now have access to big data online. In a single minute we have a huge amount of data created in social media networks alone. In fact, 90% of the world's data now was created in the past year. How much data on your therapy area or brand is created in a day? Or one week? This is a huge opportunity to really take advantage of big data. If used properly, we now have one big market research project going on in real-time, 24/7. We are already creating data mining applications to take all text data from social media discussions, write AI algorithms to analyze it, and put a host of constantly evolving insights into a dashboard that analyzes it all in real-time. Then this can be integrated into your big data integration engine easily (if you have one; if you don’t, speak with me about getting a plan to get that sorted). When you mix the strategy with the big data and the opportunity, and add AI, you can do so much more than most companies in the Pharma space have even considered. Things you could know with just this social media analysis tool are: - determine who are real influencers - predict future influencers - know what it is about your brand/s that is hindering uptake - perceive threats to your brand - gain insight into your competitors - improve brand perception and engagement - understand what caused any spikes in traffic and predict what you need to do if it is a potential problem brewing - know who may be thinking of moving to a competitor - know what content your customers are more engaged with (and by combining this with your other data, you can also strengthen the details on who should get what content to move them up the adoption curve - spot emerging trends
2. Integrate the siloed data companies have from all the separate tools – e.g. Veeva, Salesforce, Marketo, and Radian6, IoT data, device sensor data (including needle sensor data for injectibles), etc. Each tool is in a silo and the data from all the tools are not integrated well enough to provide a 360 degree view of the customer when this 360 degree view should be one of the core responsibilities of the digital teams. Admittedly, this is not a quick easy task. Eularis was recently tasked with helping create the blueprint for the integration of data for a company for numerous platforms, in many countries and numerous brands in each country (many old, some new, and some pre-launch). Then the internal team could take over the blue print and implemented it. The technology to do this varies and it is simply a matter of understanding the companies systems and objectives as to which technology stack is best to use e.g. Hadoop (and do you go for Cloudera or MapR or HortonWorks), Cassandra, MongoDB etc. Eularis have created a map of all the different technology options for each component of the stack. There is no one-size-fits-all approach. Each component has pros and cons depending on your data and objectives. However, that is just technology. The really interesting bit comes from what you can do once the data is combined, and that is where we excel. Because people don’t understand the parts, it is easy to get stuck on the technology, but the real differentiator for companies is not just about technically combining all the data (everyone is doing that and you ought to be also) - the real question you should be focusing on is ‘What are my business challenges and goals, and what data combinations and algorithms do I need to solve these and meet the objectives?’
3. Apply advanced Artificial Intelligence (AI) analytics to the integrated data with the purpose of providing transformative insights that will change the game for a company so they know not only what their customers want and need, but how to meet that need in a profitable way for their company. By applying Artificial Intelligence to your data, you can pull out critical insights previously unavailable. Think of the way Amazon offers you personalized suggestions based on past behavior. Whether you purchased, put an item in a cart but didn’t purchase or put an item on a wish list, Amazon’s algorithms uses this data to display similar types of offers to you. As Pharma marketers with a strategic eye to your marketing, you realize the power of predicting your customer’s interests, including what aspects of a message will engage and influence a specific physician or patient at specific points in their customer journey, and which sequence of channels and content are needed to move people along the customer journey faster, and keep them committed to your brand. With the client previously mentioned, once the data was integrated, we were able to write unique AI algorithms to solve many of their stated business problems including predicting physician switch, sales rep message suggestions for individual reps and understanding real influencers and not just the traditional KOL’s and a whole lot more.
4. Integrate the insights into a strong strategy that assists the brand teams. As mentioned above, it is about the right content at the right time in the right sequence and channels. This is not the domain of content management systems, as you may think. Content management systems were certainly a great leap forward but the flaw remains that most of them rely on humans to make hypotheses about their customers, and set up their personas based on market research data and simple linear rules. However, by integrating all your data platforms, then applying Artificial Intelligence to gain a 360 degree view of your individual customers, you can understand trillions of different pathways that your individual customers make (that is why you cannot rely on linear algorithms for this as the process is not linear and the data is seriously Big Data.) Also, these algorithms can be updated on-the-fly in real-time as different influencing aspects happen in your customers’ lives. Thereafter, this can be set up to feed into your content management system and your CRM to your reps to deliver real value in all channels.
You can see that when you get excited about basic descriptive things like traffic, likes, length of engagement, retweets and Klout scores, you are not seeing the kind of transformative results that could be achieved if only you integrated this information, real time information on what people are saying, and all the digital tools and applied a real AI strategy to your marketing.