Advanced analytics can boost ROI of small and midsize businesses

If you have a business, you probably have done some marketing. Maybe you have outsourced the marketing efforts to an agency. In any case, have you ever wondered if you have managed to squeeze every single drop of sunshine goodness out of the resources you spent on the marketing campaign?

Sure, one direct way to think about this is to look at the increase in sales. It’s a no brainer, the more sales, the more sunshine goodness in your glass! However, if you only look at sales as the outcome of your marketing campaign, you’ll have very little info on everything else that might be happening at the same time.

Here’s the wastage in your marketing dollars:

When you approach marketing your business solely with upping sales in mind, you’re not getting all you can from your investment. You’re throwing away at least 50% of the resources you spent on the marketing campaign because all the data that comes with running and completing a campaign is left unanalyzed! What a waste!

There is a lot of data generated when you launch and complete a marketing campaign. And for you to truly squeeze every single drop of sunshine goodness from the campaigns, you’ll need to analyze, learn and turn the insights from the data into activities that generates immediate ROI for your business. This is, in my humble opinion, the most straightforward way advanced analytics can help boost your ROI.

Here’s a simple example on how you can get more insight from your marketing campaign:

Let’s take a simple email marketing campaign as an example. From the campaign, let’s assume that you only collected email addresses with no first names or other information because you like to have as little friction as possible for your clients to sign up for a demo of your service. You have generated 1257 new leads from the list of emails but no direct sales yet.

What else can you learn from your list of emails?

Here are some insights you may be able to extract just from the email list itself:

1. The gender of the subscriber
2. The company the subscriber represents
3. The industry the subscriber works in
4. The potential level of “interest” a subscriber has to your service and maybe the subscriber’s personality

For brevity, let me expand on #1, the gender of the subscriber. If the email is composed of a name (e.g. alexandra.eames@gmail.com), the name can be used as a proxy measurement to decipher the subscriber’s gender. How do you do that for 1257 emails? This is where predictive analytics can help. By using a model built to predict gender based on names, it is possible to predict the gender of your subscribers based on their email.

How is this insight useful? Imagine knowing that more females as compared to males have signed up for a demo to your service. Wouldn’t you adjust your tone of voice, among others, when communicating with them? What about personalizing some of the service towards their unique pain-points? I’m just scratching the surface here but I hope I have demonstrated to you the upfront value of advanced analytics when applied to your marketing data. Data that you already have!

Feeling overwhelmed? Please don’t be. Check out my previous blog post to help you get started: 3 Things Small and Midsize Businesses Must Know Before Investing into Advanced Analytics to Increase Business ROI