Key features of Pega Customer Decision Hub

Andrzej – Hi everyone. I am very excited to host this little chat and find out what exactly does the Pega Customer Decision Hub Foundation mission cover. My name is Andrzej Panfil, I am a senior curriculum developer at Pega, currently focusing on Pega NLP and Process AI. I was very curious what you will be learning during this training session as participant; so, I was thinking how to best find out, other than talking directly to the man himself who was teaching the same content at Pega World! So let me introduce you to Miki Muzsi, who has been with Pega for more than 20 years, currently being the curriculum owner for Pega Customer Decision Hub and Data Scientist. Welcome Miki!

Miki – Hi Andrzej, thanks so much for having me. I am very happy to answer any questions you may have. 

Andrzej – That’s great, so let’s start with a simple one: who is the target audience, who do you think should take this training course? 

Miki – Well, so, since this training is meant to cover the Essentials of Pega Customer Decision Hub, I think that a variety of people could benefit from it. So, if you are a business leader, technology professional, a member of the marketing operations team, or even a Data Scientist – somebody who is looking to transform your decision-making processes and focus on driving better customer experiences, then I believe that this training is for you. 

Andrzej – I see, so, that is indeed a wide group… And what if I already have some experience using Customer Decision Hub? Would you still recommend it?  

Miki – Well, it really depends which version you have used. The other day, I was chatting to a former instructor, who used to teach Customer Decision Hub few years ago, and he was literally blown away when I’ve explained him the latest product features. So, during this training, you will obviously experience the latest released software, and we will cover things like Next-Best-Action Designer…[interrupted]

Andrzej – Ok wait, wait, before we dive into product features, can you maybe just explain in simple terms what this Customer Decision Hub is all about, so that participants can have an idea what do they sign up for? 

Miki – Yeah, you are right, I tend to jump quickly into features since I am really excited about them. So very simply put, Pega Customer Decision Hub is revolutionizing marketing. In a traditional approach, marketers search for potential customers from a database based on target demographics, geographies, financial means to make a purchase a product, and then they would identify a so-called customer segment, which is a subset of the total population, and then they target all these customers from the segment, across all channels, by sending them ONE specific offer. And the problem with this approach is that, only a low percentage of customers respond. So, while marketers may hit their short-term goal, in the long term, this approach will affect the relationship with customers.  

Andrzej – Ok, so what you are saying is that the traditional mass-marketing techniques that use segments, batches, and campaigns are not working anymore as they have become outdated and inefficient, right? So, what is the solution then?  

Miki – Yes, that’s exactly what I am saying. So, nowadays, the market has centered around real-time technologies and one-to-one customer interactions. At Pega, we call this capability, “1-to-1 Customer Engagement”, which enables companies to transition their marketing away from traditional one-to-many campaign-driven approach. And this is where Customer Decision Hub comes in the picture because the Customer Decision Hub forms the core of the customer engagement platform.  

And what you will learn during this training is how the Customer Decision Hub combines analytics, AI, business rules, customer data, and data collected during each customer interaction to make intelligent decisions; decisions which we call next best actions.  

Andrzej – Wow, next best actions, that’s some interesting stuff! Is there a way to get our hands on it and practice what we have learned? 

Miki – Of course! During the training, you will do some hands-on challenges, and experience how these next best actions are delivered across multiple channels. You will see 2 use cases: how next best actions are presented in the contact center, and on a digital channel, on the web.  

Andrzej – Ok clear, now, so very simply put, the Customer Decision Hub is really a centralized brain used by every channel to deliver next best actions to the customer, right? 

Miki – Yes that’s right.  

Andrzej – Ok, so you mentioned also analytics and AI. Will you go into more details on this during the course?  

Miki – Yes, absolutely. However, before we talk about AI, you will first learn about the Next-Best-Action Designer in the Customer Decision Hub portal. So, you learn how NBA Designer is used to create a set of actions, which will eventually be delivered as next best actions, and the set of engagement policies which are a set of business rules and practices that the organization uses to determine which customers qualify for which actions. Once we cover engagement policies, we’ll talk about AI and Arbitration.  

Andrzej – Ok, ok, AI and Arbitration, that sounds pretty interesting. Could you maybe explain more about how AI and Arbitration are correlated? 

Miki – Yeah sure! So, arbitration is all about applying a relatively simple formula, to arrive at a priority calculation. And the action presented to the customer is the one with the highest priority. But one of the most relevant factors from the arbitration formula is the Propensity, which is calculated by AI. So, at Pega, we use AI not for self-driving cars or for generating a nice poem…  but we use AI to determine this Propensity, which is the likelihood of positive behavior, such as the likelihood of a customer accepting an offer or the likelihood of a customer clicking on a banner. For a new action, this propensity starts at 0.5 and as the system learns about customer behavior it continuously changes and adapts in real-time, without any involvement from a marketer or a data scientist.  

Andrzej – It sounds like there is a lot going on in the back end. Is there a way to see how these values are calculated so that we have a full transparency of this process? 

Miki – Absolutely. And this brings us to another feature you will learn about, the Customer Profile Viewer, which was recently introduced in the product. Among many other things, Customer Profile Viewer allows you to simulate a decision for a customer and get insights into how the decision was made. Specifically, you are able to inspect the Propensity details, and understand which are the predictors that increase the propensity, and which are the predictors that decrease the propensity of a given action. 

Andrzej – Oh wow! It feels like a lot of details and a lots of new product features will be covered. So, you mentioned Next Best Action Designer, Customer Profile Viewer, you told us how to explain the influence of AI and so on. But let me ask you this: What is your favorite product feature, or what would you call as ‘the coolest feature’ which we will learn during this training? 

Miki – Well, in my opinion, there are a lot of nice features in the product, but one of the most exciting one, recently introduced in the latest product version is Impact Analyzer. This is really, really an exciting new feature and it’s great to see it in the product.  

Andrzej – All right, Impact Analyzer, what a cool name! Now you made me very curious. What does this Impact Analyzer do? 

Miki – Well, it basically gives no excuses to marketers, or, to the next-best-action operations team to say that they don’t understand the value Customer Decision Hub brings.  

Andrzej – And why is that?! 

Miki – Well, that’s because, Impact Analyzer allows you to monitor the overall health of your next-best-action system, and directly see how effective it is. It basically allows you to assess if your AI delivers you lift or not; in other words, it allows you to immediately see how much better off you are, using next-best-action and the AI models. And if you notice some issues in the lift charts, it helps you identify the root cause of them… as it makes clear suggestions where to look for improvements… And much related to this, are the usage of simulation tools like Scenario Planner which allows you to test alternative strategies or alternative configurations and see which one is best for your business. Or Value Finder simulations, which allows you to identify underserved customers, and then suggests actions for improvement – like adjusting engagement policies or creating new actions. But there is really so much more cool stuff I could talk about… 

Andrzej – Alright, alright! I can see that. That’s great. So, let’s summarize all this. To conclude, I will learn what next best action is all about. I will also learn about Next Best Action Designer, Customer Profile Viewer and then about AI driven propensity and action arbitration, correct? 

Miki – Yes!

Andrzej – And finally, I will see how Impact Analyzer (which is your favorite feature) and other simulation tools work, to ensure a healthy next-best-action system, right? 

Miki – Spot on, absolutely right … and actually much more! So, if you are as excited as I am about all these product features, go ahead and get your Customer Decision Hub Foundation badge today!

Andrzej – Alright, thank you so much for joining me today, Miki. And to those of you watching, if you want to see more episodes of tech talk, go to the video library on Pega community and once again thank you for joining us today!