Understanding AI's Potential in Online Growth

One of the biggest questions we get right now relates to AI.

Everyone is discussing it and we often hear things like …

• Will it take my job?

• It’s great for research, but it’s not creative

• Image creation is cool… if only it could get the details right

• As a tool, it’s only as good as it’s user

It’s clear not many people really understand how to most effectively use it at this stage.

This reminds us of the complexity many businesses face with online growth—it’s not new, but it has many layers and crosses various skill sets , so it becomes quite complex.

A Real-World Scenario: Reducing Churn in a SaaS Business

Let's explore applying AI in a practical scenario Chris recently encountered. Details have been changed slightly to respect business privacy.

Scenario: A SaaS business was doing “OK”, but knew their churn rate needed to come down. They wondered if AI could help.

• Objective: Reduce churn rates using AI

• Method: Analyze customer data from CRM systems and viewing patterns to predict churn

• Action: Initiate personalized campaigns targeting at-risk customers

• Outcome: Decreased churn rates, increased revenue

This is a great example where AI was incredibly useful in analyzing an existing data set with clearly defined objectives.

The AI was able to identify key predictors of cancellations and churn and to suggest target approaches.

All in all, this AI-assisted campaign was a huge win.

So, what does it take to be successful with the current slate of AI tools?

Let’s dive in a little deeper on our case study above to what would be needed in a similar scenario to bring AI into the mix.

Step 1: Define the High-Level AI Application and Benefits

Application: Analyze data from CRM systems, transaction records, and online interactions to predict customer actions, including likelihood of cancellation.

Benefit: Craft personalized marketing strategies to improve campaign relevance and timing, driving online growth.

Step 2: Define the Tools and Skills Required

Required Tools:

• CRM System: ex: Salesforce, HubSpot, etc.

• Data Analytics Platform: ex: Google Analytics, Amplitude, etc.

• AI Platforms: ex: BigML, DataRobot, Google Cloud AI.

• Marketing Automation: ex: Mailchimp, HubSpot, etc.

Required Skill Sets:

• Data Scientist: Machine learning, statistical analysis, Python/R programming.

• Data Engineer: Data integration, ETL processes, cloud services.

• Machine Learning Engineer: Model deployment, API development, MLOps.

• Marketing Automation Specialist: Email marketing, personalization.

• Strategic Analyst: Data analysis, reporting, business strategy.

Step 3: Define Any Implementation Steps Needed

1. Data Collection: Gather data on user interactions

2. Feature Engineering: Create features like "days since last login" or “support calls,” etc. if they don’t already exist

3. Model Training: Use Google Cloud AI to train multiple models

4. Deployment: Deploy the model and integrate it with the CRM

5. Campaign Execution: Trigger personalized email campaigns

6. Monitoring: Track and refine the campaign's impact on churn rates

Now, It’s Your Turn…

We’ve shared the above to help you assess your business and online growth situation as it relates to AI.

• Can you define an outcome for AI in terms of driving your revenue growth?

• Do you know the steps required for the AI to achieve this task for your business?

• Do you have the required tools for data collection, analysis, and outcome?

• Do you have the necessary skill sets?

AI is going to have a powerful influence on our business world, but it’s going to take time.

Just like trying to drive online growth today, while we all want it, it’s complex.

The same is true with AI.

But don’t make the mistake of ignoring it. It may not be perfect yet, but it’s the future and it’s coming faster than anyone expected.