You’ve learned about marketing automation, you’ve created a marketing plan, and you’ve implemented it. What’s next?

You need to know how to review your marketing automation data. Periodically reviewing the data and results from your marketing helps you:

  • Course-correct as you go along, ensuring that your marketing is as effective as possible
  • Learn more about your customers
  • Collect data so that even if a marketing experiment “fails,” you’ve learned something that you can use in the future

Sounds great, right? Let’s get started:

When should I audit my marketing results?

Figuring out when and how often to evaluate your marketing campaigns is something of a balancing act. On the one hand, you want to review your marketing results often enough that you can identify trends and adjust your strategy before wasting time or money. On the other hand, you don’t want to be reviewing so often that there isn’t enough time for a pattern to form.

Whenever you’re looking at the aggregate data (which is just a fancy way of saying “lots of information”), you need to gather enough data points to reach statistical validity. If you work for an enterprise company that gets thousands of customer interactions every week, then reviewing your data once a month would likely be fine. Looking at a data set with tens of thousands of points can help prevent sampling errors.

On the other hand, if you work for a smaller company that only gets a handful of interactions every week, you’ll have to wait longer. With smaller data sets, one or two interactions ending in a sale doesn’t necessarily indicate a larger pattern.

In general, it’s a good rule of thumb to review your marketing results when:

  • You’re about to switch to a new tool. This is especially important if you won’t be able to access the data in your previous marketing tool after switching.
  • You’re about to try a new strategy. That way, you can compare your current marketing strategy to your previous marketing strategy to see which one works best.
  • When doing quarterly reviews. If you don’t have another reason to review your marketing results, the end of the quarter is a good enough reason on its own.

What should I look at when doing a marketing audit?

No matter how often you do a review, your review should consist of:

Return on investment

Your return on investment (ROI) is the amount of money you make after spending money on something. It’s usually expressed as a percentage.

For example, if you spend $500 on ads and get $3,000 in sales as a direct result of ads, your ROI is:

($3000 – $500) / $3000 = .83, or 83%

Getting an estimated ROI is relatively easy, as you can see – all you need is your marketing spend and your marketing results. You can read more about calculating your ROI here.

Depending on how tight your resources are, you may want to account for labor costs when calculating ROI. If you’re running an agency or a similar business, where clients are billed based on your employees’ hours, this isn’t really useful. However, if you’re not billing based on hours, then factoring in for the cost of labor when calculating ROI can give you important insights. Something that’s free but very time-consuming may wind up being more expensive than something that costs money, but runs on autopilot while doing so. After all, you are paying your employees for their time! (This is where time-tracking tools or timesheets can come in handy.)

ROI by campaign and channel: When to track it

In addition to looking at your overall ROI, it can be useful to track ROI by campaign or channel (or both).

Campaign-based ROI is great to keep an eye on if you have multiple campaigns running at the same time – maybe you’re running a promotion on your golf-related products, but also running several event sponsorships. Tracking the ROI of those individual campaigns lets you know which was the most profitable, so that you can do more similar campaigns in the future.

Channel-based ROI is useful for the same reason – knowing which channels perform the best can help you create a more effective strategy. (This is why the MarketingHub planner reports include ROI by channel.)

Marketing KPIs and metrics

As you might remember from our post about creating a marketing plan, KPIs are “key performance indicators” or specific metrics of success. The marketing KPIs for your business will depend on your goals and priorities. For example, if your goal is to increase customers by 20% in Q3, your KPI would be the number of online customers. If you’re working to improve marketing efficiency, hours spent on marketing per week might be a good matching KPI. At any given point, you’ll likely be tracking between three and ten KPIs that are tailored to your current goals and activities.

In addition to tracking those KPIs, it’s also a good idea to track other, broader metrics, regardless of your current goals. This gives you a benchmark and helps you see overall growth or decline.

The overall metrics you look at might include:

  • Conversion rate, which can refer to two different types of conversion: from visitors to leads, and then from leads to sales. It’s always expressed as a percentage. If you send an email campaign 100 leads, and 15 of them become customers, the conversion rate for that campaign is 15%. If your landing page has had 500 visitors, and 50 of them become leads, that’s a 10% conversion rate.
  • Cost per lead (CPL), or the average amount of money you’re spending to acquire a new lead. For example, if you spend $500 to drive traffic to a landing page that collects lead information, and you get 250 leads as a result, your CPL is $2.
  • Cost per customer (CPC) or customer acquisition cost (CAC), or the average amount of money you’re spending to acquire a customer. This can be calculated by taking the amount of money spent on marketing during a month/quarter/etc. and dividing it by how many new customers were acquired in that time. It can easily get more complicated, though – learn more about how to accurately measure and calculate it here.
  • Customer lifetime value (CLV, LTV, or CLTV), or the average amount of revenue you get from a customer over their entire time with you. It’s important to keep track of this while tracking your ROI, because you may find that certain activities or channels have a higher immediate ROI but a lower CLV, or vice versa. Learn more about CLV here.

Channel-specific metrics

While most channels can be evaluated using the common metrics above, as you dive in deeper, you may want to look at some channel-specific metrics as well.

Two examples of channels that have their own metrics are email and PPC ads:

For other forms of advertising or direct mail, most people track success by giving customers coming through those channels a specific URL to go to, a specific discount code to use, or both. You can calculate how well the ads performed by looking at how the visitors to that landing page behaved or how many people used the discount code.

You can also look at the broader metrics like conversion rate and cost per lead, and segment them by channel. Do people from certain channels buy more? Where are the most loyal customers coming from? What channel draws in customers with the highest LTV? By keeping track of these metrics, you can focus your efforts on the channels that get the best results.

Trends and correlations in the data

After you’ve collected all the data, you can chart it and look for trends. What you’ll be looking at here will likely be specific metrics tracked over time, to see if they’re increasing, decreasing, or holding steady. Some of the metrics you’ll want to look at this way include:

  • Sales
  • Traffic
  • Leads
  • Conversions

For all of these, you can look at the total number, as well as the metric segmented by campaign or by source (traffic that’s related to your spring sale campaign, for example, or traffic that comes from Facebook).

Remember: correlation isn’t causation

When you’re comparing your statistics, you may notice correlations. For example, you might notice that a spike in traffic from Facebook coincides with a spike in sales. It’s tempting to immediately assume those two things are related, but if you’ve ever taken a statistics class, you’ll probably remember that correlation doesn’t equal causation. (If you want a visual example – or several – of this phenomenon, check out these charts of spurious correlations.)

Not jumping to conclusions means recognizing that the Facebook traffic may not necessarily have caused the sales, and that you’ll need to investigate further before you propose any blanket theories. If your marketing automation software tracks all visitors and their activity at every stage in the funnel, then you’ll already know whether those two things are linked or not. If you’re not at the stage of using marketing automation software, or don’t have access to those features, just make sure to test your assumptions, which brings us to…

Checking your assumptions

Once you’ve collected all of this data and compared it to previous marketing audits, you can review your assumptions and theories to see how they line up with the data.

Create a hypothesis

For example, let’s say you created a customer persona. Based on that persona (which was hopefully created with data, but if you’re a newer business or don’t have the resources to do market research, you may have had to make a few guesses), you assume a lot of your potential customers are hanging out on Facebook. You suspect that these users will convert more readily than generic SEO traffic.

Test the hypothesis

To test this theory, you create a marketing campaign that uses organic traffic from Facebook and Facebook shares, as well as paid Facebook ads. After three months of running these Facebook campaigns, you may review the data and discover that your hypothesius was correctL the traffic from Facebook converts at a higher rate than organic SEO traffic. Building on that, you can begin planning other ways to test and optimize your Facebook strategy to drive traffic and sales.

But maybe you discover that the traffic from Facebook doesn’t convert as well as organic SEO traffic. In that case, don’t think of this experiment as a failure – instead, think of it as a learning opportunity. This is a great time to think about why you came to the assumption you did. With this example, you might ask yourself questions like:

  • What data made you think your customers would be on Facebook?
  • Is it possible that those customers use Facebook a lot, but rely more on Facebook groups than the main feed?
  • Could it be that those customers don’t use Facebook at all to make purchasing decisions?
  • If they aren’t using Facebook, what are they using?

Think about what you want to change

Maybe you need to try a more organic approach, where you join Facebook groups and focus on being genuinely helpful (occasionally mentioning your products, without too much self-promotion). Or maybe you can take some of the resources you had previously allocated to Facebook, and use them to test a paid Twitter or LinkedIn strategy.

The great thing about marketing automation is that, over time, you’ll always collect more data. By looking at the data you have available, creating a theory based on that data, and then testing the theory, you’re constantly iterating towards a more successful marketing strategy.

Reviewing and updating goals

Now that you’ve looked at all of the data and at your previous assumptions or theories, it’s time to look at your goals. For your previous goals, look at:

  • Did I meet the goal?
  • If yes, does that prove any of my theories, or does more investigation need to be done to prove/disprove a theory?
  • If no, what did I learn? What kind of data was I able to gather as a result of trying to meet this goal?
  • How am I going to incorporate what I learned into the next set of goals?

While setting goals for the next month, quarter, or year, ask yourself:

  • Is this a realistic goal? It’s okay to stretch yourself, but you’ll want to show consistent results that increase over time rather than falling short of unattainable goals quarter after quarter.
  • What are the success metrics for this goal? Which metrics do I want to increase (or decrease), and by how much?
  • What theory or assumption am I testing with this goal? How will I gather the information needed to test that theory?

Reviewing not your marketing results and your goals on a regular basis ensures that you’re consistently moving the needle on the metrics that matter. After all, that’s what marketing is meant to do.

Marketing Channels: Cross-Channel Marketing Strategies and Examples
Zoho products mentioned on this page: