Why AI for Marketing and Sales?

Follow the money to see why marketing and sales are the most common applications for AI.

Instant Payback
Small improvements in marketing and sales can produce large returns quickly. Think of the impact of gaining a few percentage points on lead conversions, forecast accuracy, content targeting, and ad performance. Knowing which customers will buy, what they will buy, and when they will buy delivers value on both revenue and cost sides of the ledger.

Plenty of Data
More information than ever is available in CRM, marketing automation, and customer data platforms. AI—in the form of Automated Machine Learning (AutoML)—is really good at finding patterns in all that data to predict the future.

Easy
AutoML does not require programming or formula creation in order to make accurate predictions. Models can be made and refined rapidly. This is particularly important in supporting nimble marketing and sales processes.

AutoML insights for marketing and sales are easy to monetize and straightforward to execute. That makes them great places to amplify the benefits of AI.

Your Data Does Not Have to Be Big

Your Data Does Not Have to Be Big

In fact, certain algorithms work well with smaller datasets.

Some models do require big datasets to deliver significant predictive power. But don’t assume that you need hundreds of feature columns or millions of rows. We’ve seen surprisingly usable accuracy from as few as a hundred rows and a dozen columns.

Data is Different. AI Must Be Too.

Experiment.

The whole point of using machine learning is that AI is better at finding patterns in data than legacy methods. Try different algorithms and see if you converge on reasonable prediction accuracy with whatever data you already have at hand. AI may or may not produce actionable predictions.  Regardless, you’ll learn a great deal about how much data and which features will ultimately make you most successful.

Get started now. Waiting for your fantasy, all-encompassing datasets will leave you permanently behind the curve.