7 Steps of Online Marketing Success Through Analytics

online marketing

Determining how to optimize your business’ online marketing sales funnel can be a tricky thing. Perhaps you know something is wrong, but you’re not sure where exactly you’re struggling. Perhaps you know where you’re struggling but aren’t exactly sure how to improve.

I feel your pain.

This article and presentation will give you 7 simple steps you can take in order to achieve measurable success in whatever part of your sales funnel you need it. I’ll also give you a real-world hypothetical (that of a lead-conversion issue within a SaaS company) so you know exactly how each step could work for your business.

Let’s get started.

 Step 1. Identify the Problem

Your business’ issue can be any under-performing area – poor client retention, high bounce rates, trouble with social monetization, low conversions or an inaccurate sales funnel. It’s essential that you be as specific as possible when determining the extent of the issue.

For instance:

Let’s say that your SaaS business sells CRM software. You’ve noticed that, while your lead generation is awesome, you’re struggling to convert those leads to a final sale. “Identifying the problem” would be you checking each step of your sales funnel for holes. Perhaps you find that your initial “Thank you” email has a great open rate but miserable click-through.

There’s your problem.

 Step 2. Ask the Questions

Generate a set of questions that help you determine what you need to know in order to fix your marketing issue. This may mean you need to examine new analytics.

For instance:

You know where your problem is: an unacceptable bounce rate for your first “thank you” email to your leads. What you’re not sure of is what’s causing it, or how you can address the problem.

This is where you ask yourself the pertinent questions. Questions like:

  • Can we address this issue simply and internally, or will it require outside assistance?
  • Is this issue contained to one area of your sales funnel, or is it more pervasive?
  • Can we adequately see where (and how severely) this issue is affecting us?
  • Can we see, with concrete metrics, the effect any changes would have? (If not, you may need to update your analytics or come at the issue from a different angle)
  • How much time and energy do we estimate it take for us to solve this issue? (Occasionally, you’ll have to take a temporary hit because devoting the necessary time, energy or resources to solving the problem aren’t worth it)
  • Do we think there is enough data available for us to establish a reasonable hypothesis about solving this issue?
  • Etc.

 Step 3. Amass Data

Utilize case studies, A/B test results, analytics and best practices to get a solid base of data from which you can draw concrete, real-world expectations.

For instance:

You check out email marketing best practice articles. Read up on Mailchimp’s recommendations. Examine case studies from around the web. You establish a solid list of articles, case studies, and statistics that give you a fair idea of how to optimize that first thank you email (the one everybody’s bouncing off of in the first couple seconds).

 Step 4. Come up with a Hypothesis

Based on data, what your competitors are doing, case studies done in the past as well as strategies that have worked for you, you make a testable hypothesis.

For instance:

You decide, after reading Wishpond’s article “8 Steps to Write Email Copy that Converts”, as well as taking inspiration from a social media post that had awesome engagement, that your best option might be to include a personalized letter from your business’ CMO, introducing themselves, the business, and thanking leads for their email. You’re confident that this personal approach will increase the chance of a lead reading through and acting on your email’s CTA.

 Step 5. Test your Idea

Implement your hypothesis, comparing it to your previous results or a “control”. Continue to test for a set period of time or until statistically significant data is gathered (when your result is 95% likely of beating the hypothesis or control).

For instance:

You use your existing CRM (or whichever mail-out service you’re using) and send 50% of new leads your previous, standard “thank you” email (the control). The other 50% receive your newer, theoretically optimized email (the variation).

You run this test for about three weeks, as you’re only receiving about 25-50 leads per day and, in order to get statistically significant split test results, you need at least 750 leads.

Step 6. Analyze your Results

Compare the results of your hypothesis to your control, or previous results. Remember to measure the relevant ROI with the formula:


For instance:

After the three weeks are over, it becomes apparent (with 98% certainty) that your variation email has a higher click-through rate. Awesome!

However, before you start jumping for joy, you remember that you need to measure the relevant ROI. How much time did your CMO and copy-editors have to spend writing the thank you letter versus the amount of time spent creating the standard email you used before. Is the increase in email conversions worth the extra time and energy? Will you write different letters for each lead source?

First you establish the increase in revenue you get from the change you made. Then you put a dollar value on your time (and then multiply by how many times you have to do write an email, and then divide that number by how many leads will be seeing the same email). Subtract that dollar amount from your revenue, and divide by that revenue. If your result is more than one, you’re looking at a positive ROI. Congrats!

 Step 7. Implement the Solution

Even after implementation, you still need to keep an eye on your results. A/B test results can be skewed by aberrations caused by people familiar with your site appreciating change more than actual optimization.

For instance:

You write a few more personalized emails for different lead sources and implement them across your marketing email campaign. You watch your results for the first couple weeks, checking periodically against your previous click-through-rate.

 Rinse and Repeat

Never be satisfied. Online marketing is a constant push for better engagement and better optimization. Every landing page can be optimized better. Every social campaign more effective. Every email marketing strategy more efficient.

For instance:

Your change to the automated “thank you” email increased click-through-rates by 20%, to about 8% overall. But…

  • What if you included a headshot of your CMO?
  • What if you included a signature?
  • What if you put a customer testimonial into your emails?
  • What if you promoted a podcast, free demo, webinar or gave leads free entry to your social sweepstakes?
  • What if you asked for a Follow on Twitter or Facebook?
  • What if you put a count-down clock on a certain deal your business is running?

The list goes on. Once again, never be satisfied.


Hopefully this presentation and article gives you a more concrete idea of how to work with your analytics to achieve success.

Analytics are what make online marketing and advertising a whole new world. No longer are business’ confined to putting out newspaper ads, radio ads, posting fliers or sending a rainforest of hard-copy letters to promote their business. No longer do you have to HOPE your efforts have helped your business. With a comprehensive analytic system and the knowledge to ask the right questions, you can KNOW your efforts have helped your business (or not!)

By James Scherer