4 Things To Look For In A Customer Data Platform

Blog

Aug 14, 2018

StellarAlgo

There are many marketing tools that you can use to help you with your business. One of the most interesting, and more recent ones to be developed, is a Customer Data Platform (CDP). A CDP helps you to pull all the data from your siloed marketing tools that do not talk to each other into one place – a pain point many of our customers have expressed having. They also usually improve traditional marketing workflows, a bonus feature that helps with efficiencies at many organizations. A big reason the customer data platform concept is catching on so quickly is that they are built to make your data both accessible and actionable in order to generate measurable ROI on your data systems. Good CDPs can connect directly to source systems, existing data warehouses, or some combination thereof.

So – what should you look out for when selecting a CDP to ensure you get the right tool for the job?

1) How easy is it to get the platform up and running, and how soon will you start to see ROI?
This one is a bit hard to answer pre-implementation, but there are some signs you can watch out for that should indicate if the platform will achieve your desired time to value..

First and foremost is the data relationships and integration capabilities that your Customer Data Platform provider has. Do they understand your industry? Do they have established relationships with the technology systems you currently use? As you start to check these boxes, your expectation for a quick, effective implementation process should increase.

The next biggest sign is the level of hands on support you receive from the team behind the platform during the evaluation process. Are they quick to respond to your questions? Are they honest with you about the capabilities of the platform (key phrase to look out for: “we are working on implementing that feature and it should be available in the next few months”)? Do they take the time to work out an evaluation and implementation plan with you? Do they have an established Service and Support team to help with adoption? Aligning yourself with a product team that is driven to grow with you will ensure that you maximize the value of your investment, and will also help you remain flexible in meeting the demands of an always evolving data landscape.

Another question to ask your potential vendor is about time frames – not just around how long an installation / implementation typically takes, but in their experience, how long does it take for people to start seeing ROI on the platform?

2) What is the ease-of-use for the platform?
The reason you are deploying this platform is to make your job easier and to highlight enhanced revenue opportunities that you may not have been tapping at their full potential before. But, if the system is difficult to use – list pulling functions are time consuming, reporting functions exist but don’t give you the information you want, it’s difficult to figure out the user interface, etc. – it won’t actually get used. As you familiarize yourself with the CDP, build an understanding of the steps it takes to complete key actions – how quickly can you get answers to your questions, and how easy is it to take action on those questions?

It’s important to remember that sometimes organizational leaders and decision-makers may be reluctant to use platforms and software that is too difficult to figure out. This also extends down to all levels of the organization – essentially if someone is not a data scientist / analyst they need to be able to use and understand the platform. If it’s too complicated to pull relevant information so that it can be leveraged properly, and they have to rely on the power user of the system to pull this info, there will be no buy-in from your organization and your ROI will be low. Find a CDP where everyone within the organization can be a power user in order to truly democratize the data and drive system adoption.

Much of the success of data-based decision-making comes down to a cultural decision on the part of every decision-maker to embrace and own analytics as it pertains to them and their organization. Analytics is very much a horizontal band that should cut across the organization as opposed to standing alone. If the CDP is too complicated to use and adopt, the benefits of a unified, cross-organizational culture will not be fully realized.

3) Does the platform employ machine learning methodology and data science?
When all of your data is feeding into one centralized hub, the opportunity for insights from that data is multiplied. This is because the behaviour trends of your customers can be tracked more widely, across your multiple tools and channels. Because there are multiple data sources and data points, the predictive insights that are a key function of all CDPs are also more effective, as there is more data points that algorithms can ‘crunch’ to identify potential marketing opportunities.

Bonus: These algorithms will also help you save time, as they run automatically instead of you having to pull the data manually. Instead of taking days to combine and sift through the data, the CDP you choose should be able to automatically identify these opportunities and then report back on their effectiveness once the action is complete (don’t worry, we will revisit reporting later on in this post!).

Because CDPs are so new to market, some of the earlier ones weren’t built with machine learning methodologies, so you will need to confirm with your vendor that this is something native to the system and not simply bolted on as an afterthought. . Some CRM and Data Warehousing providers have gone this route but we offer a word of caution here.

4) What are the reporting capabilities of the platform?
The faster you can get your CDP up and executing, the sooner you will begin to see some ROI. But, how will you know that the tool you just implemented is functioning effectively?

One key characteristic that you need to review is the reporting capabilities of the platform. As we mentioned earlier when we discussed machine learning, reporting on the effectiveness of the opportunities identified by the platform and the actions taken on those opportunities are important features to make sure exist natively on the platform. The world moves quickly now and you need insights into what actions are working and which aren’t so you can optimize your data decision-making.

Another component of this is the robustness of customer attributes that can be derived from the data. Not just transactional and behavioral attributes that are obvious and native to source systems, but the creation of new attributes, customer segments, and clusters that will ultimately allow you to better target the right customers with the right messages at the right moments are also essential. Attribute derivation is an important data science capability that the best CDPs have a solid vision and grasp on.

Another good reporting capability to look out for that is not a traditional ‘report’, is how fast the system can respond to a query you have asked. For example, with regards to marketing, timing is everything. So if you’re looking to improve season ticket holder retention at a sporting franchise and you request a list of people to market to, the platform should be able to get you that info in time to ‘strike while the iron is hot,’ as they say. Once you have inputted what your goal is, the system should also be able to report potential missed opportunities for revenue (at StellarAlgo, we call these StellarMoments).

“[CDPs] are the foundation of the emerging, digitally savvy marketing organization that not only has that 360-degree view of customers but also actively engages with customers across the channels of their choice.”(1) With this in mind, if you aren’t considering implementing a CDP, what’s stopping you?