Predictive marketing is the industry buzzword of 2018. This is despite statistics that show the majority of businesses have not developed the martech stack to properly use the data. According to a report from SAS, 93% of companies cannot properly use predictive analytics. Many of them mistakenly offer the same products or services over and over to the same customers and prospects, annoying them to no end.
A martech stack properly infused with AI-driven customer-facing campaign execution seems to provide an answer to this issue. Why? Human error in outreach and unsophisticated CRM account for the majority of errors in the use of predictive analytics. This is especially true in retail, where many products have similar descriptions (e.g., grey distressed jeans vs. blue-grey distressed jeans), but it is also applicable for B2B businesses.
The current generation of predictive analysis
Today’s predictive martech stack includes aspects of traditional business processes, blockchain and AI. This is true of enterprise level companies and forward-thinking SMBs. When properly tuned and deployed, predictive marketing allows for better lead scoring, more cost effective ads, precise buyer profiles, reduction of churn and a more precise defining of internal KPIs.
How does AI work itself into this equation?
Most aspects of the technical process can be somewhat automated with artificial intelligence. The biggest advantage is that you can scale your results without scaling your expenses. This leads into the crux of what most businesses are thinking about if they haven’t looked into AI seriously.
How much is this going to cost me?
The entire purpose of AI is to bring you exponential results, so the cost of incorporating it into a predictive marketing structure is honestly moot. However, you can be assured that it is within the fixed budget of even the smallest startup SaaS microbusiness.
Moreover, the cost of AI is getting lower as we move into a world where AI is the norm rather than a luxury. If having a purpose-built AI process is too expensive, look for apps that have incorporated AI into their frameworks. Match these apps with your greatest needs, and you have a better process that does not require you to pay the premium of an obviously modified martech stack.
Here’s the bottom line. You can get AI campaign execution to help orchestrate your predictive marketing efforts. It’s time to upgrade from the “throw it in a spreadsheet” mindset that allows you only the opportunity organize your manual effort and look back in time on your numbers, not forward. And no, using One Drive and Google Sheets is not an upgrade! Make sure the solution you choose combines a precise CRM backend with a precise customer-facing account-based campaign strategy and uses AI to exact specificity and eliminate human error in targeting and execution.