Eli Lilly and Company and Aktana discuss the end of the POA cycle as we know it as the life sciences industry begins to shift towards agile HCP engagement. Learn about:
  • Modern pre-call planning: same data, new opportunities to engage
  • Personalization in pieces: thinking differently about the assets you create
  • A roadmap for coordinated execution: uniting sales and marketing with one set of business rules


Webinar Transcript: 


Hello, everyone and welcome to today’s webinar, The End of the POA Cycle as We Know It: A Shift to Agile HCP Engagement, presented by Aktana. I’m Joe Keenan, contributing editor to FierceMarkets, and I’ll be your moderator.

Our speakers today are Jay Borowiecki, Vice President of US Customer Success for Aktana and Ryan McGinnis, Capabilities Lead, Oncology Marketing with Eli Lilly and Company. You can read their full bios on the right side of your window.

Just a few technical notes before we begin. The webcast is being streamed through your computer, so there is no dial-in number. For the best audio quality, please make sure your volume is up. You can find additional answers to some common technical issues located in the help button at the bottom of your screen. The webinar is being recorded and will be available on demand within 24 hours after the event. We will follow the presentation with a Q&A session. Please submit your questions using the Q&A button on the left side of your screen, and you can do that throughout the presentation.

All right. That covers it. I think we’re ready to begin. Jay, please go ahead.

Jay Borowiecki:

Thanks, Joe for that introduction and thank you all for taking the time to join us today. For those who aren’t familiar with Aktana, we’re the leader in decision support in the life science industry. Through our software and customer success services, we’re helping our clients institute a new way to go to market. Our team not only helps implement, but we play a consultative role in helping clients get the full value of our solution.

But what we’re talking about today is this change in go-to-market execution. Companies like Lilly are recognizing the need to become more dynamic and responsive to our customer behaviors and market changes, plus the need to be faster and more relevant, or, in other words, they need to be agile.

So, today’s discussion’s going to focus on the shift we’re seeing more and more companies take towards this more agile approach. By the way, when we’re talking about agile, we’re talking about it in a sense of how sales and marketing needs to be more flexible, nimble, and current when executing their strategy. We’re not talking about an agile approach to software development, which our product and development team can speak to at length. That said, we’re going to begin by reviewing the difference between this traditional versus a new kind of agile approach.

Then, we’re going to get into three areas of focus, which are plan, act, anticipate. Then, during these sections, we’re going to provide some more scenarios and examples for you.

By the way, the insight and example that Ryan’s going to share on the Lilly’s approach is based on his work in the oncology space. However, much of what we talk about today can be plied across any therapeutic area or brand. As Joe mentioned, at the end, we’re going to take some questions.

All right. So, let’s jump into it. We felt that the timing of today’s discussion was appropriate since many of you are probably returning from or getting ready for your national sales meetings or POAs. As many of you know all too well, there’s a lot of time and effort that goes into this overall approach from strategy and budget planning, that generally starts in the summertime, to program and content development with your agencies, to then, finally rolling it out at your POA meeting.

It’s at this point that we see things get put into motion. Reps get their marching orders. Marketing programs and campaigns commence, but we traditionally see that, once it’s out the door, teams are making minimal adjustments to the execution plan and not really updating it until the next cycle begins the following year. It’s kind of that classic set-it-and-forget-it approach.

However, the marketing place isn’t remaining constant and your customers needs are ever changing as you can see from this blue squiggly line. So, as a result of this traditional approach, what we don’t see is data being acted upon as often as it should be. Although data is being used to drive this initial strategy planning process, it’s rarely used then to optimize the ongoing execution because without the right technology, there is a lot of manual effort analysis required. Thus, no action is taken.

We also tend to see a disconnect between your sales and marketing execution. Again, during the planning stages, we see both sales and marketing working together towards these common goals and challenges, but when it comes time to execute, they tend to work separately.

Then, finally, while there’s a lot of feedback out there, they don’t always see it being acted upon because it’s either not systematically collected or, if it is collected, it sits in disparate systems that don’t talk to each other.

So, as a result of all this, what may have looked like a great plan at the beginning of this cycle is no longer aligned to your customer needs as you roll out your execution. There’s typically no plan to really adjust this until that next cycle begins, so there’s a big disconnect.

Well, we believe that the best solution to this problem is to move towards an approach where sales and marketing are more agile and focus on making continuous improvements in smaller but quicker updates over time, which is why we feel it’s the end of the POA cycle as we know it.

Companies like Lilly are shifting away from this set-it-and-forget-it approach, because they recognize that they need to stay relevant and timely to meet their customer needs. They’re responding to changes in the market rather than just following a plan. As a result, the plan is constantly being adjusted to stay in line with their customers, as you can see with this red line here.

But in order to do that, there are some things you’re going to want to consider. First, your planning process doesn’t have to be completely scrapped, but it does need to be modified. Go through your normal planning to identify your key strategic imperatives and do your budget, hold your POA event, but set expectations and create execution plans that can be adapted based on change and timely data. If you’re going to continuously improve, then your content and your messaging needs to stay fresh and relevant, too.

I know regulatory view can be challenging here and you don’t have an unlimited budget, but modular templates can help. Doing this will help you move towards subsegmenting and then eventually to a more one-to-one personalized plan at scale where, for example, each HCP receives a custom message sequence rather than a predetermined sequence.

Then, finally, ensure that you’re integrating your feedback loop into your system that enables you to respond to changes and improve upon your execution strategy. This is where decisions support technology and machine learning are important because it quickly evaluates loads of data and serves up what’s relevant and valuable while using the feedback to optimize the execution over time. We believe that these are the key considerations that allow you to be more agile. However, there is no one way to do this, nor do you have to have it all figured out to get started. What’s important is to get started so you can begin improving your customer experience as quickly as possible.

With that, I’m going to now turn it over to Ryan, who’s going to talk a little more about why this approach is important to you and to your customers.

Ryan McGinnis:

Yeah. Thanks, Jay. I’ll preface with by no means have we completely figured out how to do it. It definitely is a continuous learning process for us as well. So, if you think about how what we’re all striving for. That is obviously better HCP engagement. How are we going to use this process to get us there? What we’ve done is we partner with Aktana. We create suggestions for sales reps based off of business rules. We try to leverage the data we get back from that in order to continuously learn, ultimately improve our strategy and get to better HCP engagement. The way we do that is we use those suggestions and we use the data that comes back, like dismissals. How often does a sales rep act upon this suggestion or business rule? How often are they dismissing it? Which gives us crucial feedback to give back to the brands as they think about how they’re going to build their strategy and execute it through those business rules.

Ultimately, that allows them to tweak it, to personalize it a little bit more, add in new data, edit it where they need to, which gives better suggestions to our sales reps in time. Ultimately for them, for a sales rep, that just kind of “feels better.” It feels like the right suggestion at the right time.

But now they’re engaging more often, which creates a better strategy execution for us. As they’re leveraging these suggestions more often, that’s ultimately more shots on goal with our HCPs, which raises our engagement as well, because they are getting individualized suggestions to them, relevant to what’s happening for them right there. We’ve continued to tweak and improve on the process.

So, Jay, that’s a little bit about how we look at the process to continuously learn.

Jay Borowiecki:

Thanks, Ryan. Now, that we’ve set the foundation, talked about the differences between this traditional versus new agile approach, we thought we’d start focusing on these three areas where we can share some of our experiences. Again, these three areas are plan by using a single roadmap to execute, act on dynamic info, and then anticipate the information needs of your customers.

So, we’re going to first start with the plan. So, at this point, I’m going to turn it back over to Ryan. He’s going to talk a little bit more about how they’re aligning their sales execution to their strategy. Then, I’m going to walk you through a broader approach.

Ryan McGinnis:

Yeah. So, we’ve kind of looked at it in maybe four different buckets of how we think about executing our strategy within this capability. The first is the fact that we have suggestions and how that helps us execute strategy on a more frequent basis. The example I like to give here is that in our kind of traditional approach, how we used to do things is we would have a national sales meeting or POA once a year, maybe twice if we had some new indication or some big change in the marketplace or strategy. The brand gets up on stage, they give their strategy for 15 minutes or so, “Here’s what it is. Here’s why we came up with it.” Sales reps go back to their breakouts and they practice the messaging for a little bit and talk about it. Then, they’re out in the field and they’re having a conversation with their customers. It’s 6, 9, maybe 12 months before they’re back in front of the brand hearing that downloaded strategy. There may be some small touch points in between, but largely, it’s a kind of set it and forget it, to use Jay’s words, of brand strategy mentality.

There’s a lot that happens in the meantime there. The customer asks questions that takes the rep in a different direction. Marketplace changes, new data comes in. A lot can happen, and maybe even a sales rep got through the messaging and has actually had a great message. Where did they go next?

So, with our suggestions on a daily basis to the sales rep, that allows us to have almost a daily touchpoint within strategy, which gets our execution much tighter.

The next part is the data. I really look at this within two different realms. One of them is the fact that we can actually use this data and add in segmentation, add in other data points to really fine tune and filter and make it a personalized suggestion, both for the rep because it’s relevant and it’s right for them and it makes sense to them, but also for the customer because it’s the next step for what the customer needs.

The second part of it is really kind of “bigger data.” I don’t mean this in the sense of an Amazon bigger data, but we’ve been able to use bigger datasets than we previously did because we can take a bigger data set. We can use the business rules through Aktana to create small bite size, almost digestible next step suggestions that a sales rep can actually act on. So, we’ve moved from a large data set that largely we’re not able to act upon to something that we can give to a sales rep and they can know exactly what to do next that very next day.

The next part is personalization. We partner with the suggestions with approved email, so we’ve got personalization on two levels. The first is the personalization of the suggestion itself. We can leverage the factors in the business rule to really segment and make this a really fine-tuned approach and next step, but when you add in approved email to those suggestions, as an action that the sales rep can do and even free text to a certain extent, now you’re getting a personalized action with a personalized delivery or content for that customer.

Then, the last one is insights, which is really almost a bit of an internal focus here and, as I mentioned before in our continuous learning exploration, as we get a lot of this data, how often a sales rep acts upon a suggestion, dismisses it. Why did they dismiss the suggestion? Open rates of emails. That provides us a wealth of data that we can go back to the brand team and continuously learn with and back to even the field on how they can execute it a little bit better.

So, those are a few different ways from a sales perspective that we’re trying to help align strategy. I’m going to talk a little bit about the brand side as well because there’s some changes on the brand side that we’ve been focused on, as well. So, I’ll get to that in just a minute.

Jay Borowiecki:

Thanks, Ryan. As Ryan mentioned, he’s always looking to better align their sales execution to their brand strategy, which is, of course, an important step, but I would like to take a step further and talk a little bit more about how some clients are breaking down these walls between sales and marketing execution and moving away from this siloed approach. But the ultimate goal is really to try to transition from this siloed approach to a fully integrated plan. We need to have a single journey instead of business rules that puts the customer at the center and then uses this data and technology to drive that next best action across all channels.

Yes, I recognize that this is an approach that’s difficult and challenging, but there are companies that are already moving in that direction and some are already integrated. However, since getting to this ideal state can be difficult, there is an easier step you can take to get started immediately. That’s at least making sure that both sales and marketing execution is coordinated. Taking this approach would at least bring some visibility into each side’s activity through the exchange of information so in doing so, your reps are going to have a little more information on what the customers are receiving and engaging with from your marketing teams. In turn, the reps could then use that information to better serve their customer overall. You could also say the same thing on the marketing side. You could use some of the rep feedback to optimize those ongoing campaigns.

So, I want to kind of step back a little bit and go back to this integrated approach. I like to share an example of how you can incorporate the field force into this marketing campaign or journey. So, if you imagine the situation a few months after your POA, there’s a significant shift in payer access. As a result, one of your HCP segments lost coverage. They went from 100% and dropped down to 80. Then, her patients were now required to pay a co-pay. You want to act quickly, so an email campaign to target HCP makes sense because you can provide both information about that change as well as you can provide a link to request some co-pay cards.

So, what we traditionally see here is something like this, where you have an email that goes out to all targets. If the HCP doesn’t open, then a resend goes out. If the HCP did open, request a co-pay card, that’s great. So, they mail the co-pay cards. However, if they didn’t. If they opened, but didn’t then request co-pay cards, then another resend email goes out trying to get them to engage. However, you don’t always know why exactly they didn’t engage.

This can all work, but why not involve the sales force and take this two-pronged approach that allows you to not only act quickly, but increases the changes of engagement through a more personalized approach? Maybe instead of a marketing handling the resend, you have the rep do it by sending an approved email, which is a little more personalized. If the HCP opened the email, but they didn’t request that co-pay card, why not send a priority suggestion to that sales rep for them to then visit the HCP and discuss the needs of a co-pay card or not, again, providing a little more of personalized touch, but also adjusting some of the challenges or concerns that that HCP may have about either the formulary change or the co-pay cards, again, getting a little more feedback as to why they didn’t request it in the first place.

Then, finally, for those HCPs who did request the co-pay cards via the email, which again is great, but you may want to take it a step further and make sure that the sales rep is informed of this action by providing an insight that they can use at their next follow-up.

This type of approach are solutions that Aktana is helping customers achieve today by integrating their marketing automation campaigns with decision support that allows companies to respond quickly to these changes while providing a little more relevant and personalized experience.

So, we’re now going to move into the second principle, which is act. I’m going to hand it back over to Ryan. He’s going to talk a little bit about how Lilly is acting upon this dynamic information, allowing them to be a little more agile and, in turn, helping drive new business.

Ryan McGinnis:

So, the way we’ve been thinking about it is how do we shift from just dumping data to a sales rep, maybe our kind of traditional approach where you give a sales rep sales data, you give him brand strategy, you give him HCP segmentation, some marketing insights to go along with that, all to be done compliantly in a conversation. A sales rep is a very high-quality person, but they’re not a marketer. They’re not a data analyst. They’re not a market researcher all in one. So, that’s a lot of information for a sales rep to just try to digest as they go back out and have their conversations with their customers. So, what we’ve moved to with this more agile approach is how do we leverage a lot of that data to then almost as a personal assistant to filter through that and actually distill it down to what do I need to do next with this customer based off of what’s important for them?

You can still use all that data. In fact, as you can see here on the right side, we actually can start to leverage more different types of data. The complexity of our business rules can get very high, but the ultimate output to a sales rep is a very simple next step action. We can change that data in and out, so it’s an agile approach in that not only is it a personal assistant to them of here’s what the next step is, I took all that data for you and I figured that out for you, but we can tweak it as we go, as well. That is a little bit on the sales perspective.

We’re also, as I mentioned before, changing the mindset from a brand perspective as well. So, a few shifts in mentality for them. One is, instead of building a single comprehensive piece that a sales rep would leverage that goes to the whole message, we’re working to try to get more volume, smaller pieces. This fits along with a personalization aspect, so if I can break out a message into tiny, bite-size pieces, as a sales rep, I feel like I’ve got the opportunity to tailor exactly to what my last conversation was or what the need is here. I’m not giving you the whole thing. I’m giving you what you need that’s relevant at the right time.

The next part that we’ve switched away from is creating content only when there’s a new strategy available and then kind of throwing it out and it’s out there and we’ll work on the next part of the strategy. Instead, what we’re trying to focus on is how can we make this an agile environment? We do quarterly releases, quarterly updates, which allows us to do things like seasonal content or content that might match up to marketplace events. If there’s a conference in the spring, we can create content for the sales rep or that conference and in the summertime, we can pull it back and get ready for the conference in the fall and get some content to help engage their customers ahead of that conference. So, moving from a one-stop this is a strategy and we’ve got the strategy out there and it’s all encompassing to bite-size, over time, relevant to the current events at the time.

The other part that we’re working on is moving away from each brand, building this in their own silo and how can we leverage this across our portfolio? The way we do this is we’ve created templates. Jay alluded to this early on in the conversation. We create templates that help us create efficiency. We go a lot quicker because we have the same template and each brand can drop in what they want to. It also creates a consistency both for the sales rep and for the customer. Sales rep knows what the email is going to look like as it goes out the door. Customer see it, says, “This looks similar to other things I get from this company, as well.”

The next one here is a one-and-done mentality. This isn’t just, “Hey, I’ve got the brand strategy. I got it out the door,” but, “I got this tactic done, this piece of content done and it’s out the door. And now I’m focused on the next one.” Instead, we try to leverage the opportunity to have A/B testing because we have these quarterly releases. That gives us small windows of time where we can test something and we know that we’ve got another opportunity to get something out the door quickly after that.

So, in the springtime, we can put a piece of content out that’s got some minor differences between two pieces and we can see which one wins because we’ve got the data analytics, which reps engage the most, which one had HCPs engaged the most. Then, in the next quarter, we can go back and use the one that won to better iterate and become more agile with our content.

Then, finally, working on leveraging the backbone behind a lot of this portion here is leveraging the data behind the tactics. Because we can see which suggestions, which business rules were acted upon by sales reps, which ones were dismissed, why, which emails were opened, which ones were not, that gives us a ton of data to leverage, to not necessarily have to start from scratch and build a new piece of content or a new business rule, but rather just iterate and tweak along the process. So, those are some examples both from a sales rep perspective and from a brand perspective on how we’ve focused on changing some of the mentality.

One of the examples I want to go into just a little bit deeper is this A/B testing. This is something that one of our brands actually did at launch as they were coming up for launch and maybe to give a little bit of the context and the back story. This is related to both our suggestions and the call to action of sending an email.

As we started to get email content out for our sales reps, the feedback that we consistently got back was, “This is great. We love being able to send email and personalize it with some free text. Please, give us as much free text as possible so we can make this a personal message from us and it doesn’t sound like a canned message from the brand that them and every other HTP received in a blast email.” That’s what the continuous feedback that was knocking on our door as we came to this launch and the brand then decided to try some A/B testing.

So, in this scenario of a launch brand, what the brand did is they had two pieces of content, two emails that they put out, exact same content within the body of the email, but the difference was in the subject line. One of them was this free text subject line that reps had been dying for and keep asking for. The other was an MLR, medical legal regulatory approved, subject line that contained brand name and now approved, things that sales reps could not type on their own within the free text.

What we actually found was reps in that two-week period that we looked at this, this email was sent about 4,500 times, but reps chose almost two to one actually the pre-approved content subject line, which completely flies in the face of the feedback we had been getting. Ironically, however, customers opened not quite two to one, but significantly more the free text subject line.

So, this is an example of A/B testing that we could take back both within the content, but even that we do within our business rules and our partnership with Aktana to say, “Hey. How can we continue to tweak here? What situational learnings can we take back to our brands whether it’s in a launch situation or other situations that have a similar type of need here?”

So, Jay, I just wanted to dig in a little bit more on one of the examples we’ve got here.

Jay Borowiecki:

Thanks, Ryan. We kind of went through the first two principles here, plan and act. For the third one, we want to focus on how we’re anticipating the needs of your customers. Then, I’m going to focus on how reps anticipate the needs of their customer’s HCPs. Then, I’ll turn it back over to Ryan with maybe a little more examples from Lilly.

So, in the age of big data and one-to-one marketing, it is critical that sales and marketing are staying current and flexible so you can anticipate your customer needs and serve them that information that they find useful and valuable at that right time. This is why it’s important that we look at ways to modernize the rep’s pre-call planning process, so it’s not only up to date, but it contains this helpful information. In doing so, we’re going to allow them to react a little more quickly to changes by staying current to the latest trends, strategy, and messaging and preparation for their next detail.

So, let me give you an example. Maybe as a rep, you’re not scheduled to see Dr. Jones for another two weeks because you’ve reached your goal of, say, five calls this quarter. However, a priority suggestion pops up in your CRM because Dr. Jones has a new patient that was just diagnosed in the last couple of weeks who would be a primary candidate for your product. You go ahead and schedule a call.

Then, during your pre-call planning, you review an insight that Dr. Jones’ market share has been decreasing since your last visit, which further assists you in preparing that message you want to deliver to Dr. Jones. This is an example that highlights the importance of utilizing intelligent technology that allows your reps to act and adjust quickly to changes and updates through streamlined and simple platform that can provide reminders, time savers and these what we call like aha moments that, without the technology, probably would have resulted in a missed opportunity.

I’m going to turn it back over to Ryan, who’s going to share a little more example of this on his end from a patient journey.

Ryan McGinnis:

Yeah. Thanks, Jay. I’ll give an example of how we’re acting within the patient journey but also how we’re leveraging some of our business rules for a continuous learning cycle and also create more opportunities as well. So, we’ve got a product. Let’s say that it’s indicated in second-line treatment as you can see here within the patient journey. That red dot indicates where our indication is. To date, we’ve been working off of a first-line treatment decision as a data point to give to a sales rep to make sure that their engagement is in time to prepare for that second line decision.

So, that green and white dot there represents what we’re hoping in our past example or in our past history where we hoped to create an engagement for a sales rep by giving this data point.

So, as we started this journey with Aktana to start to build business rules, get the data back, understand what’s happening and make adjustments in our cycles, one of the first things we’ve learned from sales reps is that …

Well, let me take a step back here. We also want them to obviously follow up, post a treatment decision on an action here but one of the first things we’ve learned was they were actually dismissing this suggestion to go have this interaction. The reason was they didn’t give them enough time to actually get in and have an appointment before that treatment decision happens.

Clearly, we needed to actually get some kind of data point earlier in the patient journey of a diagnosis, which is ahead of a first-line treatment decision that allowed them more opportunity, more time to set up that appointment for that discussion to prepare for that second-line decision.

That was first learning there that we got back, which then led us, as we further built within Aktana and our business rules. We then added in approved email. It led to a whole bunch of opportunities for us. The first part is that we could use that first data point now as a suggestion for an email. It’s creating an initial interaction to start the conversation. We could then create suggestions based off of segmentation and other data points to actually pull that middle interaction there into three different interactions. Then, we could have follow-up interactions that could be very differentiated next steps here, then they acted on this in a certain way. That then leads to this next step action, which ultimately became very specified for us.

Now, we could say, “Send this email because this customer has a patient.” Then, you could say, “Here’s message one. Have this interaction.” Depending on how that interaction happens, you could then move onto message two, message three. You actually have a treatment decision. Then, you can get very differentiated in what the follow-up looks like.

So, we move from a single interaction, single engagement that, quite honestly, wasn’t appropriately timed for primary execution with a sales rep to a better focus towards the sales rep and when to execute it. Much more specific in next-step actions and making sure that those actions were really correlated with what was happening on the patient journey and in the HCP’s mind.

So, Jay, a little bit of a deeper example there. Both patient journey-wise, how it fits together. Also, our continuous learning, and then how it’s created more opportunities for us, as well.

Jay Borowiecki:

Yeah. That’s great. Thanks a lot, Ryan.

So, in summary, the modern approach to executing your strategy involves more frequent adjustments and changes as you’ve heard today. You’re being more responsive to your customer needs and behaviors. We believe that companies that are moving towards this agile execution approach are going to find themselves more engaged with their customers to make smarter decisions, which are going to help them achieve greater results.

But some of the key takeaways from today are use technology to take a data-driven approach to your execution, which is going to help allow you to automate and quickly serve up these customer-specific next steps as Ryan was talking about.

Once it’s automated, then use machine learning and insights to learn and improve. Again, it’s an iterative process. You’re going to want to anticipate your customer needs so that you can serve them the timely and valuable information that they want and need. As Ryan was saying, keep the content fresh by updating and delivering in these small, bite-size pieces. Hopefully by doing all this, you’re going to start seeing things, so you should start seeing a more steady and consistent impact to your strategy, execution, instead of these peaks and valleys that are often seen by taking this traditional approach.

Again, what’s important here is that you just get started. Hopefully, what we’ve provided you with today are some good ideas and how to just do that. Thank you. I’m going to turn it over to some Q&A now.


All right. So, we move onto the Q&A presentation segment. I’d like to remind the audience, there’s still time to submit questions using the Q&A button at the bottom of your screen. We already have a lot of great questions and we’ll try to get to as many as we can in the time remaining.

So, I’m just going to throw this out to the both of you. “What kind of data sources are you using to create suggestions for the reps? Is it just CRM data?”

Ryan McGinnis:

No. It’s a good question. I’ll go ahead and start with this here and, Jay, feel free to chime in on what you see outside of our work.

I’m not going to get terribly specific on it, but in general, treatment data, whether it’s sales data or whatever it may be, we do use CRM data. So, what the sales rep has done, calls that they’ve had already, appointments scheduled, to the extent we can, we’re trying to leverage segmentation data and even some broader marketing data kind of outside of the non-personal channel.

Jay Borowiecki:

Yeah. Just to kind of add to that, it’s of course CRM data, as Ryan was saying. We see a lot of clients with sales data, marketing data, a lot of third party sources that we work with. So, there’s multiple data sources that we can work with here.


So, the next audience question is, “How are you getting more feedback that allows you to make frequent adjustments to execution?”

Ryan McGinnis:

Yeah. I’ll go ahead and start with this one, too. Probably a variety of different ways. First, as I kind of mentioned throughout a little bit, we really leverage the suggestion and the dismissal reasons. So, as we put suggestions out there, sales reps can act on them or not act on them. If they don’t, there’s a brief survey within the dismissal that gives us some feedback as to why they don’t. We do like to keep in contact with a small group of the sales reps on our small team. Helps give some of the color commentary behind some of the data points as well, so as you look across the actual data, you provide some color commentary in there. It really quickly paints a pretty deep story of what’s working, what’s not working, where we want to start to focus a little bit more, and, as I mentioned, we do this roughly on a quarterly basis, so that provides us a lot of opportunity to continue to churn and change and update.

Jay Borowiecki:

Yeah. Just to add onto that, as Ryan was saying, it’s really important that we’re utilizing the data sources as well as the feedback. As he was mentioning, it’s important that as we provide suggestions that they’re either acted upon or they’re dismissed. Even if they’re dismissing it, it’s important feedback for us to then be able to make sure that we’re capturing that and adjusting as appropriate as needed, so it’s getting back to that feel right, that Ryan was talking about before. So, even though it may not be something that the rep wants to do or doesn’t feel it’s appropriate, it’s that feedback that we need to then use and improve upon for future.

Ryan McGinnis:

Yeah, and I’ll add back in, too. We’ve communicated pretty heavily to our sales team that a dismissal is equally important as an action sometimes for us because it gives us the opportunity to improve. That message to a sales rep alone I think means a lot because, one, they kind of realize that, “Hey, you’re not telling me I have to do these things. You’re giving me the option.” But, two, they see their internal partners as being open to listen and change and adjust, as well. So, I think that point Jay makes about communicating the importance of a dismissal is really a big one.


Okay. Next up, “Is the solution based purely on business rules or is there an AI element to provide insights, suggestions that were not thought of before?”

Ryan McGinnis:

I may not be the full expert on this one, but I’ll start. Yes, you can do all of the above. I think it’s to the extent that you want to and you’ve got an appetite for it, but yeah, and probably more importantly, you’re able to. I don’t know that you want to jump straight into an AI use case. You may kind of start crawl, walk, run type of thing. I think probably a lot of my peers outside of my company are probably somewhere in that spectrum. Somewhere, it might be much further ahead in using that, but I think you can do anything and all you want to. I’ll maybe default to Jay to keep it in line if I’ve gone too far.

Jay Borowiecki:

No, no, it’s a great question. As Ryan mentioned, you do want to kind of start with something and then continue to improve upon it so there’s really kind of three ways we kind of look at it in using AI. So, overall, we’re looking to use it to improve the overall execution, so we were just kind of talking about that before as you start to understand either using historical trend or engagement. We can help kind of start refining that so that, again, gets back to that kind of feel.

Secondly, we can start looking at it how you kind of refine your go-to-market strategy. This could be using, again, some of the feedback out in the field and then applying that to then improving that overall strategy. We can start helping predict kind of best time to engage, best routes, best messaging, et cetera. Then finally, a third way that we also look at it is looking at how we can also take kind of input from other models as well.

So, it’s those three that we kind of use AI in everything that we do here.


The next question is, “How have the marketing teams changed the way they work to provide more content in a frequent and iterative way?”

Ryan McGinnis:

Yeah. Maybe to go back to the example a little bit. I think one thing is we’ve tried to create, maybe move as much obstacles as possible. What I mean by that is I think sometimes they would like to create more content, but just where is the time capacity dollars to actually do that in process? In the regulated industry, there’s plenty of process and we’ve got a lot of that. So, where we can, we’ve created templates that help them move things through the process faster, whether it’s something that has been looked at favorably from a medical, legal, regulatory perspective and allows a quicker review, consistency across them so that everybody’s using the same templates. So, that’s from a process perspective. We’ve tried to at least provide that platform.

I think the other part is it almost kind of goes back to a brand’s business planning time frame of thinking about it as being an iterative process and a flexible process throughout the year. I’m not coming out of business plan with three or four big tactics I’m building for the next year, but I might have one or two big ones, but then I’m also going to be conscious of the time and effort and money that I want to save for doing iterative updates to email content, for example, or business rules or that kind of thing.

So, I think part of it’s a process, kind of a centralized platform process where you can remove obstacles. The other is a mindset. In doing that, part of what we’ve decided, we’ve made a conscious decision of was we were going to kind of get this minimum viable product out the door from this capability perspective. We knew the capability wouldn’t be perfect on day one, so we advertised it that way. We said that we’re going to get something out. It’s going to be in that crawl phase, but we’re going to lean on you guys, sales reps, you guys, brand teams, to help us improve this process. So, in doing so, we’re going to do this quarterly release.

I always describe it to our teams as think of the apps on your phone. Every so often, you got an app on your phone will update and you get new data. They clean up some bugs. They put some new visual in. That’s kind of how we treat this capability. Once a quarter, you’re going to get an update. We might put some new data in. Strategy might change a little bit. We might fix some business rules. Maybe some new content. That’s how we’ve advertised. I think it’s helped the brands and the field, the sale reps really, put their minds around. “This is something that isn’t a one and done. This is how we’re going to continuously improve.”


All right. “With the steady and bite-sized content, how do you rollout with sales teams through meetings, virtual meetings?”

Ryan McGinnis:

Yeah. A little bit of both, so obviously we’re not having TOAs as frequently as we’re updating this or national sales meetings or meetings of really any live meetings. We still have those. Don’t get me wrong. They’re still important to delivering a strategy providing the full picture, but we leverage our, like as I mentioned before, we’ve got a sales team. We leverage them to communicate out to their broader teams. We’ve got some regularly-cadenced communications from our internal teams to the field. We leverage some of those as well. So, it’s a little bit of a mix here and there, depending on the level of update that we’re doing at any given time.

Of course, we do spend time in our POA continuing to dig into this capability, so improving the skills, but also the information and content that goes with it as well. So, it’s really kind of across all spectrums that we can reach our field that will communicate to them regarding updates and changes and new things.


“Have you been able to measure whether the customer experience is better with this agile approach and how are you defining success?”

Ryan McGinnis:

The million dollar question. The one that our VPs like to ask us. So, yes. Yes and no, really. I think maybe … I think, essentially, this question kind of gets to almost an ROI component because that’s … We’re all ultimately accountable for that and depending on how your organization looks at that, you can define it the way you need to, but I know there’s lots of different ways to calculate ROI, so yes, you can come to that kind of conclusion. I think, as we are working through our stages of building this up, I think one of the things we look at is HCP engagement. Are we seeing an improvement in HCP engagement? Are we seeing high levels of HCP engagement whether it’s opened emails, which is kind of the lag indicator. You’ve got successful business rules that reps engage in, but you want to first start to see our reps as that … Do you have a high level of rep engagement? As you do that, you’re going to see HCP engagement go up as well, just naturally.

So, kind of our proxy, to answer your question there, of is this successful from a customer perspective? That’s how we look at it. We’ve been happy. We’ve been really happy with our level of HCP engagement, but that’s kind of how we look at it primarily, if you’re looking on a month-to-month basis or a quarter-to-quarter basis.


“What kind of validation or cleansing did you need to do on your data first?”

Ryan McGinnis:

That’s a good question. So, I might actually go back to the beginning where Jay made the comment that you got to start somewhere. That’s kind of the mentality we’ve had with this. We knew things weren’t going to be perfect. As I mentioned, we advertised that to all of our teams internally and field teams. So, we use data. We’ve got a certain level of comfort with the data we put in there to begin with, but I think probably the biggest thing that we’ve taken away is how much we’ve changed how we’ve used that data over time with the business rules, seeing what’s accepted, the suggestions, what’s dismissed, learning from it, hearing, “Okay. We see this in the data. Let’s go ask the field questions about why, kind of get that color commentary,” as I mentioned.

A lot of times, that’s told us a really interesting story about how we might be using the data incorrectly. We should think about it slightly differently, maybe add new data in, whether it’s just a new set of data or integrating that data with some of the other data pieces. We can do that now, that we couldn’t do before now that we put these business rules together and these suggestions. We can bring almost disparate pieces of information together as filters in our business rules.

So, really I think the answer is not how much validation we did ahead of time, but how much this enabled us to clean and change and think differently about our data over time.


All right. That, unfortunately, was our last question. We had a lot of great questions today and unfortunately, couldn’t get to them all due to time constraints, but we will be getting back to everyone who submitted personally after the webinar.

I’d like to thank everyone for attending this FierceMarkets webinar and submitting so many great questions. I’d also like to thank our speakers for participating and Aktana for presenting.

A reminder to the audience, the webinar has been recorded and you will be able to access the recording within 24 hours using the same audience link that was sent to you earlier. Thank you again for joining and we look forward to seeing you at future events.