There’s a lot of buzz around ROI and marketing these days. But what does it mean? What can you do with this data in your company’s digital marketing plan? The answer is, if done properly, tracking the return on investment (ROI) for every campaign will enable companies to make decisions about which campaigns work best and how they should be tweaked or changed next time.
The “marketing roi calculator” is a tool that calculates the return on investment for marketing campaigns. It helps companies measure their ROI.
Our obsession with monitoring marketing budget returns is one of the things that has enabled Slidebean to expand quickly and effectively.
When we only had around $2,000-$3,000 in marketing budget per month in 2015, getting the most bang for our dollars was critical—not just for development, but also for survival.
However, keeping track of where a client originated from may be difficult, particularly when you expand your marketing channels to include efforts that do not result in a direct conversion.
Take, for example, a Google Adwords campaign; you may trace and validate the source of a conversion by utilizing the following:
- The Adwords conversion tracking pixel.
- In Google Analytics, a conversion event.
- The URL’s UTM parameters (which we’ll go over in detail in a moment).
Customers may end up looking for your name in Google rather than hitting the sponsored link if you sponsor a podcast or a Youtube video, for example, which means you’d have no clue how they got to your website in the first place.
This is where the science of smart tracking comes in; there are hundreds of methods you can use to monitor client sources properly for every online product or service, and we’ll go through each one in this post.
Google Analytics (basics)
Google Analytics is a very useful (and completely free) tool. It would certainly destroy a lot of other analytics products on the market if it were simpler to use, but Google hasn’t done a great job of simplifying it.
Even yet, integrating and monitoring is extremely easy; all you have to do is put a small script at the top of your page.
Google will then begin monitoring everything that occurs on your site, including pages viewed, funnels, user journeys, time spent on a page, and so on. You may go back at any moment to look at previous data and answer any new questions about your user behavior that may arise. However, extracting this information is difficult.
Defining conversion objectives early on is the simplest way to approach Google Analytics. When a user completes a desired action on a website, a conversion goal is triggered.
These objectives may include:
- Visiting a single page or a set of pages (like a checkout or successful signup page),
- Spending a specific amount of time on the website, for example, or
- Sending a trigger event from your app and completing it.
Once you’ve established your objectives, you can simply filter your data to see which channels are responsible for these conversions. We can readily determine which channels generate more signups and compare conversion rates with this sample.
You may use the same method to achieve more complex objectives, such as beginning a subscription or finishing a transaction. Because the objectives feature does not enable you to look at previous data, they will only begin tracking conversions once you have put them up.
Google only allows 20 conversion goals per account, so go ahead and use them all at first, then delete and change the ones you aren’t utilizing.
At Slidebean, we keep track of the following objectives on a regular basis:
- Any plan may be converted.
- Our Individual Plan is being converted.
- Our Teams Plan is being converted.
- Purchase of a single presentation
As you can see, all of our objectives revolve on marketing ROI. You may also set objectives to track how your product or service’s user interface is doing (like watching a tutorial video or completing a form). Other tools, such as Kissmetrics (discussed later in this article), allow you to do a lot more with those kinds of funnels, such as segmenting each stage depending on a particular audience or time of day.
Parameters for the Urchin Tracking Module (UTM)
By utilizing UTM parameters on your links, you may further “educate” your Google Analytics data.
A parameter is similar to a URL’s suffix. Google Analytics can monitor the domain and address where a visitor came from whether you put a link into a Quora response or a Facebook post, but such data is seldom helpful on a mid-to-large size website.
UTM parameters are also the sole method to obtain detailed campaign data in Google Analytics from marketing campaigns that aren’t taking place inside Google’s ecosystem (Google Adwords-Analytics).
You may provide extra information to Analytics using the Google URL Builder to better monitor traffic origins. For example, if your brand awareness campaign revolves on addressing customer queries on Quora, Reddit, or Twitter, you may use the utm campaign parameter to aggregate all of that traffic together.
This is an example of a tagged URL for a Facebook ad campaign:
slidebean.com?utm source=facebook.com&utm medium=cpm&utm terms=marketing-audience-A&utm campaign=US-FB-ContentMarketing
The URLs in this article have been labeled in the following way:
slidebean.com?utm source=bplans.com&utm medium=content&utm terms=marketing&utm campaign=blog
Let’s have a look at each variable individually:
The domain (not the entire URL) where the link will be placed is typically the source. This should be facebook.com if you’re advertising on Facebook.
Medium: This is most often used for paid advertising campaigns (CPC, Cost per Click; or CPM, Cost per Impression), but it may also refer to email, posts, or content. Any CPM/CPC visitor will be immediately classified as “paid traffic” by Google Analytics.
Campaign: You’ll want to establish a campaign nomenclature and have everyone on your marketing team adhere to it, such as US-Startups or WW-ContentMarketing, so you can combine all of your conversions under one ID.
Campaign term and content (optional): only provide these criteria if you’re doing an in-depth study or if your campaign has a large number of fronts. You may use “term” to filter the terms you’re targeting, or the people you’re targeting if you’re running a Facebook ad campaign. Campaign content, on the other hand, allows you to give each version of your ad a unique name or ID. If you want to monitor anything in great detail, these are the tools you utilize.
Conversions may be tracked directly in your ad platform.
It may be time-consuming to go back and forth between your ad platform and your Google Analytics findings.
You may link your Google Analytics account to your Adwords account and cross-reference your goal conversions to your campaigns, ad groups, and even individual advertisements and keywords inside Google’s ecosystem.
This is how it appears:
Knowing which term generated a conversion is very helpful for filtering out poor keywords or optimizing for these keywords in your SEO strategy (this is how we did it).
However, since this Analytics-Adwords direct connection does not occur naturally on other platforms, it will be difficult to determine which particular advertisements are effective unless you use a sophisticated UTM tagging system.
As a result, several platforms have begun to develop their own tracking pixels. Others are simple to integrate (and some aren’t), but the majority work in the same way as Facebook.
You must include a generic tracking pixel in the head area of your Facebook pages. That pixel monitors page visits (PageView) automatically, allowing you to create conversions depending on particular pages viewed, for example.
However, using Facebook’s Conversion Events is the greatest method to monitor objectives. When a user clicks a certain button or completes a specific stage, you may utilize Facebook’s default set of events, such as “Lead” or “CompleteRegistration.” These are much more precise than URL tracking and are required if your program is a single-page application like ours.
You can use these conversions as goals in Facebook’s ad platform, so your advertisements are automatically tailored for the text and pictures that are generating the most conversions, rather than the most clicks). You may also utilize these conversions for retargeting (but that’s an other issue).
You can compare campaign ROI immediately on Facebook with Conversion Events enabled and properly configured, saving you a lot of time and work. Conversion monitoring is comparable on Twitter and LinkedIn, but their pixels aren’t as excellent.
It’s also essential to keep in mind that each pixel or piece of code you add to a website has an effect on speed and load time. Use them all carefully, and test them all on a regular basis.
Using Kissmetrics to track conversions as a pro
Kissmetrics is a great and effective tool for monitoring activity inside your app, and it’s helped us measure our marketing ROI tremendously.
If you use Kissmetrics in both your app and your landing pages, their pixel will give an anonymous ID to every person that visits your site, even if they haven’t yet registered. As soon as the user submits such information, all data points connected with that identification are saved in the Kissmetrics database and linked to an email address.
Consider the following scenario:
- User A comes to your website as a result of a Facebook ad promoting a piece of content.
- They take a look at the material and then depart.
- They came upon another piece of material from your blog while surfing the internet a month later.
- That person returns three months later to establish an account on your platform. They do a Google search for your business name and come across a Google ad that you have created, which they click to see your website.
Even if the Google Ad on step four eventually led the consumer to sign up, the campaign that got them there in the first place deserves the actual credit (in our opinion).
Because Google Analytics allocates the sign up to the previous campaign that led the user to the website, the credit/attribution for that sign up will most likely wind up being the Adwords campaign for branded searches that the consumer clicked on step four.
In Kissmetrics, on the other hand, you can look at the customer’s activity log and see that a unique ID was generated for that user in step one, and that the customer’s initial source campaign is a Facebook ad (this is transferred to Kissmetrics using UTM tags).
In Kissmetrics, here’s an example of a customer journey:
Activity and campaign sources are recorded for each visit:
All future visits, as well as the visit that prompted him to sign up, and the campaign that got him to the website the final time, are all monitored.
One significant distinction between Google Analytics and Kissmetrics is that when a client enters an email address, that email is linked to the anonymous ID generated on the initial visit, allowing you to see a specific user’s activity record.
You don’t need to look at user-specific data very often, but having it accessible is critical for fully understanding your analytics at scale. Kissmetrics offers various tools for formatting large quantities of data, but they also allow you to create customized spreadsheet reports in Excel to run your own charts and algorithms.
Promo coupons and checkout surveys are a last resort.
Some initiatives can no longer be monitored using conventional methods. If you place a billboard on the train, for example, you can direct visitors to yoursite.com/subway, but many people will just Google your brand and convert from there.
Checkout surveys and campaign-specific promo coupons come in handy here. A checkout survey may be used to monitor and verify the outcomes you’re receiving from your various marketing channel tracking techniques.
We used Typekit to create this checkout survey, and it has worked wonderfully for us. We took Squarespace’s two-question approach and used it to monitor our additional marketing initiatives, such as podcasts.
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ROI = LTV
There’s a magic LTV > 3x CAC figure for a SaaS company: a customer’s “lifetime value” (or LTV) (total income anticipated from each paying user) should be more than three times greater than the customer’s cost of acquisition (or CAC).
This may be readily computed for SaaS companies by utilizing the monthly churn rate (LTV = ARPU-Average Revenue per User/Average Monthly Churn Rate).
It’s more difficult to track lifetime value in other kinds of companies. To calculate an LTV on an ecommerce platform, for example, you may utilize margins, average transaction size, and the proportion of repeat consumers.
We just launched a product that operates as a one-time purchase rather than a subscription, so we analyzed customer data to see how many of our customers make repeat purchases and how many of them thereafter subscribe to a plan. We took all of this into account to calculate the ‘single purchase LTV,’ which is now 1.4x the initial transaction value; although, this will clearly vary from company to business.
More information on monitoring metrics for a SaaS company may be found here.
Putting everything together
Now that you have a variety of data points verifying the customer source, how can you summarize them in a manner that allows you to calculate your ROI?
To link the following data elements, we utilize a mixture of spreadsheets:
- Emails from the database with the customer ID.
- Based on their plan or purchases collected from SaaS metrics platforms like ChartMogul or Baremetrics, customers’ LTV is calculated.
- All data points collected through UTM tags and checkout questionnaires are referred to as the customer’s sources. We get this from Kissmetrics and it comprises of one to six columns.
- Revenue generated by customers to date, as reported by Stripe, our credit card payment processor.
This takes intermediate Excel/spreadsheets abilities; there are several great Excel materials online (that’s how I learnt), so Google searches are the best way to go. Rather than simply following a step-by-step instruction, it’s critical that you comprehend what you’re doing.
For example, if you Google “average values in a database column depending on given criteria,” you’ll get a slew of tutorials on how to use the AVERAGEIF function. INDEX/MATCH, COUNTIFS, and SUMIFS are the formulae that you’ll use the most.
The spreadsheets that we use the most are as follows:
Weekly/monthly summary: a generic spreadsheet with graphs to understand performance week to week and month to month.
Monthly recurring revenue per campaign: you may create a graph of how much MRR each campaign delivered for a particular weekly or monthly cohort using INDEX/MATCH.
LTV per campaign: you may compute the estimated LTV brought by each campaign using INDEX/MATCH and your estimated LTV data. Your campaign expenditure should definitely be less than this, preferably 1/3 or less.
Revenue received to date, per campaign: Using Stripe data, you can compute real charges made to each user and see whether a campaign’s expenditure is on schedule to be recovered. This is particularly helpful if you’re a SaaS business and want to track the effect of annual prepaid memberships.
Metrics are crucial, and as your company develops, they will become more complicated. When you develop a system early on, you’ll be able to expand your knowledge of the data as it gets more complex. Every week, I devote one morning to metrics analysis, trying to figure out how they changed on a weekly basis and what factors and teams may have had an effect.
Decisions based on metrics are as objective as a company can get. They have enabled us to reduce the danger of making choices based only on intuition.
The “roi tracking template” is a guide that will help you track and measure your marketing ROI. It includes the main points of what to include in your report, as well as how to use it.
Frequently Asked Questions
How do you track marketing ROI?
How do you keep track of ROI?
A: I keep track of ROI by tracking what income my customers are making for me.
What is a good ROI percentage for marketing?
A: This is a difficult question to answer since there are so many factors that it would be impossible for me to tell you what the percentage should be.
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