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The Compound Effect of Incremental Change

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We’ve all watched the following scenario play out:

A new CMO rolls into town. Soon after, their team changes. A few employees may be cut loose, and some essential contacts are recruited into the organization. Next, there’s a branding overhaul, website redesign, and new content cadence.

To be fair, a company may desperately need all of these sweeping changes (every marketer knows a good narrative is foundational). However, the more technical arms of marketing—analysts, ops, and technical specialists—often question the activity around logo and mission statement updates.

Why spend money on a logo redesign when you could dedicate resources to speeding up the time it takes sales to receive a lead and improve sales visibility into the prospects who are most likely to buy?

More people will see your logo than an infrastructure update, but they probably won’t make a purchasing decision based on the look and feel your design. However, they might give up on your company if it takes five days to follow up on a Contact Us form.

The simple truth is that mundane changes that improve conversion rates are often the most effective way to increase pipeline output.

Incremental Change Illustrated

Let’s say you have a contact database that’s being actively supplemented. You purchase a lot of syndicated content and lists from industry databases that qualify as a “marketing accepted lead” (MAL). They don’t convert well, but it’s a great way to build a database of names.

Note: Throughout the exercise, we assume the average sales price remains constant at $100,000.

conversion rate optimization

After looking at the cost of acquisition versus sales output of your contact database, you decide to move to more intentional name acquisition tactics. Webinar registrations, short-form gated content, and paid social networking are more expensive but result in a much higher lead MQL conversion rate.

MQL conversion rate optimization

The numbers don’t look great--yet. You now have 40% of your original MQL volume from 12% of your original MAL volume. However, you get some good news from sales. Because these individuals were more aware of your product when they entered your database, they’re converting meetings at a higher rate and qualifying more of those meetings into opportunities. The close rate once qualified stays the same.

conversion rate optimization

Now you’re producing the same amount of revenue from 12% of the names acquired in the first example. 

This is a dramatic overhaul, so let’s look at how smaller changes could impact your numbers.

Let’s say you decide to stay with high volume name acquisition tactics, but you hire an email marketer who is plugged into your messaging and complementary online events. She develops a strategy that engages more readers and converts more people into MQLs, raising your conversion rate from 3% to 5%.

MQL conversion rate optimization

By improving an early conversion rate by 2%, you increased your revenue output by 50%.

In a different variation, we’ll assume our email nurturing didn’t improve, but our marketing ops superstar figured out how to elevate the hottest leads to sales in a way that really gets their attention—within 30 seconds of a form fill. Due to this speedy transfer, you see a healthy uptick in meeting conversions.

meeting set conversion rate optimization

You effectively doubled your revenue by pulling one lever to make the buyer journey less bumpy.

Let’s see what happens when we make minor incremental improvements to each step in up to sales qualification (SAO):

general conversion rate optimization

By nudging each conversion point up a couple of percentage points, you’ve more than doubled your revenue. Small changes add up fast!

Why Don’t More People Start Small?

You may ask if changing a few smaller items translates into bigger results, why don’t more people focus here?

It’s a fair question, but the answer is complicated. Sometimes marketers don’t have the reporting infrastructure in place to know their conversion rates. Maybe the team doesn’t have an analyst who can dig into why a number looks bad. Perhaps they don’t know the number is below industry standard or can be improved.

The scenario I’ve seen too frequently is that the operations team is buried in technical debt and/or an ad-hoc reporting backlog, and optimizing systems aren’t a priority. If this is the case in your organization, look at where your team is spending their time. What can be done to free them up to make optimizations?

This may mean investing in a scalable reporting solution, the right talent, or contract resources to redistribute less strategic tasks.

Where Should I Start?

If you don’t have the infrastructure in place to track the buyer journey, your tech stack is a great place to start. You need to be able to measure when a lead reaches each checkpoint and calculate conversion rates. Be sure you can slice these rates by marketing channel, industry, and other major factors for your business.

Once you have measurements, check out blog posts and articles on your industry’s standard conversion rates. If that isn’t available, try joining an online group like our Master Ops community. Marketo, Eloqua, and Hubspot also have active user communities that may be able to provide input on what “normal” conversion rates look like.

Once you identify a point in the prospect journey that is looking less than stellar, you can dig into the “why” behind the number.

For example, suppose your MAL to MQL conversion rate is low. In that case, you can look at nurture track engagement, messaging, and tailoring the strategies you’re using to convert leads such as dropping low converting channels and investing more in channels that are producing pipeline.

industry standard conversion rates

If your MQL to Meeting conversion number is low, you can look at your MQL definition to determine whether you’re passing people along who aren’t really past the Awareness phase of the buyer journey. Other things to check are the time to first sales touch and qualitative feedback from the sales team qualifying the leads. Be sure to inquire about each marketing channel as results and input will vary drastically across lead sources.

If your Meeting to SAO rate is low, I’d dig into whether or not the same team is doing both functions. If not, there may be misalignment between the two teams on what a qualified opportunity looks like. If people who are setting meetings are also converting them into opportunities, it’s a great time to check to see if some people have lower rates than others. Low rates are a great coaching opportunity to help a rep understand what a qualified prospect looks like.

Don’t Leave Out Salespeople

As you inspect your prospect’s experience across marketing and sales, don’t forget to ask sales for input. They understand target audiences and what does and doesn’t work better than anyone else. Their jobs depend on it. 

With that said, use data to confirm what people are telling you. People are biased. We’re programmed to focus on the negative over the positive. If one person tells you that system administrators in the technology sector are terrible targets, do some analysis on your qualified opportunities and leads. If your conversion rates for system administrators are better than average, it’s safe to disregard the feedback as an anomaly. 

If every person on the inside sales team tells you one thing and your data tells you another, you better check your data quality. A unanimous opinion is seldom wrong.

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