No-Code AI Is As Easy-To-Use And Powerful As You Hope It Is

‘AI is not going to replace managers, but managers who use AI are going to replace those who don’t.’ – Deborah Leff, former CTO for data science and AI at IBM.

That quote probably sounded intimidating when it was said at VentureBeat’s 2019 Transform event. It was also noted that many companies were failing to get their AI strategies off the ground, and only 87% of projects were making it into production. Part of the challenge was that AI involved complex algorithms that were out of reach unless you had specialized knowledge, and the number of people with that knowledge wasn’t matching the demand. But over just a few short years, that has shifted with no-code technology. AI is now accessible to business users to execute with automated tools. 

It is comparable to the evolution of creating a website. A couple of decades ago, only developers could build a website, but now tools like WordPress and HubSpot make it possible for anyone with average computer skills. Likewise, data science execution is rapidly approaching that level of user-friendliness. With data connectors and automated machine learning algorithms, projects can be set up and run in just clicks. 

The benefits of no-code AI for your data analysis and strategic planning:

It makes your life easier. Your team won’t have to rely on data scientists or programs to run projects. No more justifying why your projects are a priority to get them moved up in the projects queue. Instead, with just a little bit of training, all members of your team will be able to create and run their own prediction analysis projects with the same powerful, insightful results. 

It will help you make the next leap. Using AI will become commonplace in business, just like it has in our personal lives (think show recommendations, flight price predictions, etc.) You can get ahead of the curve and level up your skills and the team’s skills while uncovering the insights that move business forward. 

It uncovers the opportunities your company can use to improve both sides of the balance sheet. Some of the most common and impactful use cases include: 

1. Customer churn risk identification. Score all active customers on the likeliness to churn and build custom action plans based on attributes associated with churn.
2. Customer acquisition at the macro and micro levels. With prediction, you can not only identify future customers but future customers by the item, offer, specialty, or SKU level for hyper-targeted, high-performing campaigns. 
3. Upsell with the right offer at the right time. Using past behavior, you can predict what your customers are most likely to purchase next – and when they are most likely to make that purchase. Be there at the moment they are ready with the right offer. 

For all of these use cases, your performance marketers and analysts can build these projects in minutes and re-run them as often as they like to serve your customers and meet business needs. 

Takeaway: No-code AI makes data science projects accessible to the broader team. With Squark, all you need is to identify your uses cases, connect your data, and decide who gets to press the buttons. 

For more information on evaluating no-code AI technology, check out our co-CEO/co-Founder, Judah Phillip’s article in VentureBeat, 5 critical factors to consider when it comes to evaluating no-code AI tech.