Predictive Analytics and AI are hot topics in the analytics and marketing worlds right now. Those who have been early adopters are seeing great success, but how do you know if you’re ready to take full advantage of the technology? We’ve put together a short checklist to help you determine if you’re ready for a predictive analytics solution based on what we’ve seen from our most successful clients.
We’re not asking if you’re an expert in all the principles and algorithms; that’s what we’re here for, but do you have a high-level understanding? Could you explain it to your CEO (or your mother) – just enough so they understand the what and why you’re interested in pursuing predictive analytics?
There are a limitless number of uses cases that an automated predictive analytics solution could help you solve for, that is the beauty of machine learning, but we’ve found some of our most successful and biggest named clients (UPMC, Epic Games, HubSpot) all started the same way, with a simple use case.
A simple use case, but one that is tied to your KPIs and/or revenue. For example, who from one specific program is at risk of churning? OR Who from one segment is most likely to convert?
Your data doesn’t have to be perfect, nor will you need the assistance of engineers to help you transfer your data from where it lives to Squark; we’ve automated that process too, but you do need access to the data from your end.
Squark has intelligent connectors to get your data from where it lives to Squark and back again. Once it is in Squark, our automated data preparation and feature engineering not only help smooth out any anomalies or missing data but also enhance the data with things like date factoring and Natural Language Processing (NLP).
Squark is a no-code solution designed to be easy to use for non-technical business users, but there will be a brief onboarding/training. Knowing who will be running that first project helps so we can get them up and running as quickly as possible.
*You can always add additional seats.
Squark is a very affordable solution, particularly compared to some alternative platforms or hiring a team of data scientists. However, we still have our team to pay, so no matter the solution you choose, some budget will be needed.
That’s it! If you’ve answered yes to all of these questions, you’re ready for a predictive analytics solution and to start anticipating and catering to future customer behavior to drive desired outcomes. Our team of experts is ready to help you begin your journey, schedule a demo and discuss your company’s use cases.
Judah Phillips