Expectations versus reality
When we talk to organizations about customer experience (CX) or about CX tooling, we often get the reaction that they are already working on this or that they’re quite ‘good’ when it comes to it. They managed to leverage customer data for providing a relevant interaction. However, we notice that the company’s internal expectations are rarely met. A pilot was delivered, but they are struggling with the next steps. We often hear they expected to see results sooner, but that the first use case still isn’t on point months after the launch, or that they have little overview of the various use cases and how they impact each other. The use cases should all be linked to each other as they are all meant for the same customers eventually.
A program with personalized banners in an app, for instance, needs to rhyme with the next best offer program that is launched through the call center for inbound calls. If these programs are not connected, you might give your customers irrelevant offers or miss out on opportunities. Next to that, the companies we talk to realize they need a lot more people for the setup and maintenance of the CX program department-wide, exceeding the initial budget and putting the ROI under pressure.
And all of this comes down to one impactful realization that can’t be neglected: the scalability of CX is a serious challenge to overcome. As McKinsey & Company states, “seamless customer experience can be worth at least as much as a superior product or efficient process—building customer loyalty, reducing costs, making employees happier, and boosting revenues significantly”.
The companies we talk to realize they need a lot more people for the setup and maintenance of the CX program department-wide, exceeding the initial budget and putting the ROI under pressure.
Digging deeper, we can distinguish 5 typical CX scalability issues: setting up an extra use case, maintaining the implemented use cases, orchestrating the various use cases, the infrastructure beneath the platform and the team members that have to work on the use cases. Ignoring these is not an option. You should see this as a checklist to figure out in which areas you’re already doing well and where you need to put in extra focus and effort.
As this blog post turned into quite a long read, we split the article into two: in the first part we draw the context of the market pain points and then we go over the three first challenges one by one. In the second part, you’ll find the two remaining challenges and we’ll then also dig deeper into some basic principles to overcome those.
A Customer Data Platform: fit for purpose
So here’s the good news, there’s a tool to help you conquer all these challenges: a Customer Data Platform (CDP). A ‘real’ CDP is an essential part of the martech stack if you ever want to master these key issues and scale up your CX.
Such a platform enables you to assemble all the necessary data from several systems from inside and outside the company and build dynamic, real-time customer profiles. These ‘single sources of truth’ will help you become a lot more customer-centric, as they are the source for highly relevant actions and communications, and at the same time, they give the necessary insights that make it possible to fine-tune the orchestration.
5 scalability stumbling blocks
1. New use case setup
Some platforms make setting up an extra use case just as complex and time-consuming as the first ones. Setting up the new models and automation doesn’t happen overnight so this takes quite some time to implement. Moreover, it is difficult to recollect data from various sources and there is a very low possibility you can reuse previous use cases because of their complexity. All of this making it impossible to estimate the ROI in advance.
Let’s have a look at a use case for car loan applicants. While the customer is browsing your website, a lot is happening in real-time in the back-end. Risk and pricing analyses, propensity and intent calculations, all by combining the CRM, and behavioral and transactional customer data from several sources. The customer’s DNA is updated instantly based on his online behavior and in the end, he receives a completely personalized loan offer.
In order to develop this use case, a lot of data needs to be available and connected. All well, but what happens if the next use case is going to be implemented? More often than not, organizations have to start from scratch because their platform is not scalable in this respect. What you need is a setup or a platform that allows you to re-use all the data that is already available in the platform (used for other use cases), making it easier and quicker to stack use cases.
2. Maintenance of the use cases
When it comes to maintenance, both technical and marketing maintenance can limit the CX scalability.
Technical maintenance
Imagine that a data source changes the format in which it delivers the data. Address properties, for instance, first the street name and number were combined in one field, while now it suddenly comes in two separate fields. A harsher adjustment is when a data source, such as Facebook, changes the API. Without global technical monitoring over all of your use cases, you just know something is wrong, but you can’t pinpoint what exactly.
It gets even more worrying when you are not even aware you’re having issues. This is very common when many different sources are being assembled in an unclear and spread-out dataflow. A good CDP will automatically alert you when something is not working the way it should and without such a clear and centralized view, only a few people know what is running, where and when.
At one of our telco clients, for example, we heard that in the past a use case was down for 3 months without them having any clue. They only discovered it because some team member was a client and noticed he wasn’t receiving the marketing communication he should have.
Marketing maintenance
Traditional marketing only analyzed the performance of campaigns when they stopped running or every 3 weeks at the earliest. This means the results of it were only visible after 3 weeks, which is a very long time without any tweaks. Also, the marketer addressed the audience all at once instead of running ongoing campaigns in which the moment of the offer is defined by the customer himself. The campaign banner on a specific page would then be shown only for 1 week instead of shown over a longer period of time and only to particular customers. Additionally, a certain audience was selected for the offer and multiple campaigns couldn’t run parallel. This means that when someone, for instance, was selected for a mobile data campaign but was then showing interest in a better wifi connection package, the customer couldn’t be added to multiple campaigns at the same time.
When you’re addressing people with multiple campaigns, it is important to see how the offers are performing, when they are running, how people are engaging with it and which ones are successful. Email engagement is easy to track for instance, how often did the customer open the mail or how many times did they click on the links, and then you can change the offer once they clicked more than 3 times. This performance information is required for various sections: by channel, offer, audience, etc., and should allow the marketer to take action immediately when tweaks to the offer, experience, audience, etc. are needed. Next to this, the lack of such an overview prevents the marketeer to quickly shift budgets between campaigns and stopping or scheduling them.
3. Orchestration of the various use cases
There are 3 types of orchestration that could be standing in the way of scalability: within a single-use case, between multiple use cases and the reorchestration of use cases.
Orchestration within a single use case
How can we make sure the customer always gets the right experience? Within one use case, the right customer gets the right experience, on the right channel, at the right time. But the ‘right channel’ is where the shoe pinches. Departments often have their own P&L (Profit & Loss), such as the digital department versus the offline branches. This easily creates issues as customers are usually not limited to a certain department. So whose efforts pushed the customer towards the buying stage? Thanks to the marketing team, the customer clicked on an ad on the website, but the digital team is responsible for the site, and when the customer read the online information, he reached out to the call center for additional info and finally went to a brick and mortar store to purchase the product. So the various channels are not inclined at all to click into a central system, because then they wouldn’t be able to decide what is going through their channels. And when it is time for the budget allocations, this can be quite a struggle when it’s based on the results.
Within one use case, the right customer gets the right experience, on the right channel, at the right time. But the ‘right channel’ is where the shoe pinches.
Orchestration within a use case sounds very simple to set up but this is where it often goes wrong, and because of that, the marketers can’t choose what the best offer is because the offers just aren’t available across every channel in all stages of the customer journey.
Orchestration between multiple use cases
When you have more than one use case, you need to ask yourself what the next best offer is. Which one is prioritized over another in the particular channel the customer engages on and which one gets delivered at a certain moment in a specific context? And are you all using the same information and determination engine to decide real-time on the available information based on channel, context, and historic information?
It speaks for itself that this can easily go wrong. Users sometimes receive a bunch of messages, all about different topics and with a different offer. Spamming your clients seriously damages the trust they have in you. Imagine getting a reminder to pay back your credit card debt when you already did that yesterday? Who likes to receive several completely unrelated text messages within 48 hours from their bank? That’s right, no one. You need to approach your customers with relevant messages, along with a consistent customer journey. Don’t send him an offer to change their mortgage when they’re considering getting a car loan.
So with every use case added, reconfiguration is needed for orchestration. And this only works if all use cases are centralized and if all information is taken into account for every decision that is made.
Eat, sleep, orchestrate, repeat
What happens to your orchestration every time you add a new use case? With some platforms, adding a priority sequence requires manual input. This is possible of course, but it definitely becomes harder and is very time-consuming when you go from 10 to 100 use cases. Manually determining ‘when customer X does this, he sees offer Y’, is not scalable over time.
This friction can be removed easily with a central platform that automatically takes care of the various orchestration levels for you. The ‘recommender’ continuously learns from all the available customer data, automatically and in real-time. The system individually applies the priorities for each customer and makes sure that the use cases are presented at the exact moment they need to be.
These 3 issues all have an enormous impact on the scalability of CX. Find out how your organization is dealing with this today and start thinking of a strategy to tackle these. In the second part of this article, we’ll cover the remaining 2 issues and then we’ll go over some basic principles your organization can hold on to.
