The past is super important to marketers. It’s because the story with marketing usually goes like this: First, you use some marketing tactic. Then you give it some time to generate results. Finally, you check on those results.
Affiliate marketing whatsapp number list has a simple premise. Just like Batman and Robin, vendors team up with affiliate marketers for mutual gain, making it a win-win for many business owners.
On that note, marketing analytics will help you answer questions such as:
How much organic traffic did our content generate last quarter?
How many new leads did Campaign A generate compared to Campaign B?
What was the conversion rate from trial sign-ups to paid subscriptions?
What was the average cart abandonment rate last year?
The good news is that more often than not, marketing analytics software does the tracking and measuring of the most popular metrics automatically. But the important thing is to set up those tools as soon as possible to avoid data gaps.
Analyze the present
Marketing analytics can answer some more “timely” questions too, such as things related to patterns in customer behaviors, trends, current budget spending, etc. For example:
Why is organic traffic to our blog decreasing?
What percentage of our customers use the [feature] of our product?
What is the lifetime value of our customers?
What is our current ranking for [query] in Google?
And when you’ve got insights into your past performance and present state of affairs, you’re all set to take on a task that marketers are asked to do (but few can deliver) all the time: predict the future.
Predict the future
Enter predictive analytics or, in other words, making data-driven assumptions about what can happen in the future. Predicting the future is why marketers are not simply reporting for reporting’s sake.
For example, if a marketer is able to prove a positive return on investment of a given marketing tactic based on past performance, they can forecast the future performance quite accurately. Often, this is enough to get the marketing budget they need.
Here, we also enter the realm of prescriptive analytics, the type of analytics that answers the question, “What should be done?” For example: