Customer LTV

Now, it’s time to take a look at each link in Moira’s Customer Conversion Chain. I’ve added a few initial observations for each link so you can see how you might approach a real-life situation. First, is an overview of the lifetime value of Moira’s customers.

Customer LTV = $6,600 Avg. Purchase × 3 years = $19,800

Cost-per-acquisition: Based on current data, CPA is: $50,000 ad spend / 10 customers = $5,000.

CPA seems high. It will take nine months ($5,000 CPA / $550 per month) to recover Moira’s costs to acquire each customer.

Action point: Moira should consider a pricing test offering a 10 percent price discount for prepaying the annual subscription resulting in recouping your CPA right away, affording her company some working capital to invest in additional customer acquisition or to apply to the bottom line.

Cost-per-lead: Based on current data, CPL is: $50,000 ad spend / 500 leads = $100.

CPL seems to be in line with the industry average, but who wants to be average? A bigger issue seems to be the gap between the average CPL and the high CPA. This may signal a problem with onsite conversions.

Action points: Moira should drill deeper on the attraction source inputs to see if there are clear winners and losers for CPL. Move down the Customer Conversion Chain metrics to further examine onsite conversion metrics.

ROI: We know that Moira’s company is investing $50k/month to generate about $198k in new revenues, but this revenue won’t be recognized all at once. Additionally, we ask Moira for her gross profit margin and she says 70 percent, which is fairly typical for a SaaS company. Investing $50k for $70k gross profit is the true ROI for LTV.

Revenue ROI = $198,000 LTV / $50,000 Ad spend = 396 percent

Gross Profit ROI: LTV =($198,000 × 70 percent, or $138,600) / $50k ad spend = 277 percent

Note: Now that we know the gross profit margin, the actual time to recapture her CPA is 13 months:

$550 per month × 70 percent = $358 gross profit

$5,000 CPA / $385 = 12.99 months

This suggests Moira has more than a marketing problem. She has a business problem. Under Moira’s current business model, she’ll need enough cash reserves to cover the time between customer acquisition and breaking even on her CPA. And, that doesn’t even take into account a 30-day sales cycle and the 30-day Free Trial period. That’s two more months added on to the total purchase cycle.

So to bridge the gap and sustain her company during the time she’s recouping her original investment, Moira needs 14 months × $50,000, or $700,000. Growth through new customer acquisition may seem like the obvious solution, but, ironically, taking this path only exaggerates the problem under the current situation. Obtaining more customers by spending more increases the dollars needed to sustain the company from the time between the marketing investment to attract visitor and the actual customer acquisitions from that original dollar investment. In this situation, the business will be in a negative cash position, possibly imploding as soon as growth stops. Do you see the problem here? Do you see why marketing matters?

Action points: Moira should seek efficient ways to acquire new customers or she should seek investors. Statistically speaking, that’s the best she can do. Marketing can’t perform miracles.

Customer

When a lead makes an initial purchase that lead becomes a customer. It’s important to know the average first transaction for your customers so you can figure out your marketing ROI. Here’s a look at Moira’s customers:

Customer = $6,600

Moira’s customers come in two types: Type A, who need one annual subscription, and Type B, who need two. According to Moira, 90 percent of her customers are Type A.

Segmenting these customers, it’s easy to see that one group (B) is worth twice as much on a dollar-per-transaction basis than the other group (A). Incrementally, it costs no more to acquire this lead or to communicate with this lead. In fact, Moira’s operational costs are cut in half when performing a demo, setting up a free trial, and servicing this valuable customer.

Action points: Moira should research the Type B customer, looking specifically at comparative data for significant variances against Type A, including:

• Keywords used to enter site
• Pay-per-click and click-through-rate
• Source customer used to find site (social media/SEO/PPC)
• Cost-per-lead (this could be double for Group B and still be fine)
• Cost-per-acquisition (if it’s the same, you may have just hit a gold mine — provided the market size for Group B is large enough)
• Return-on-ad spend (RAS)
• Onsite activity including time on site, page views, and pages visited
• Lead-to-customer ratio

In short, if the market size for Group B is large enough and conversion ratios are acceptably promising, Moira should perform a specific Customer Conversion Chain analysis just for Group B to hypothesize growth.

Demonstrated Interest

Moira defines demonstrated interest as a prospect who signs up for a 30-day free trial of her software. Of the people who sign up for the free 30-day trial, 25 percent become a customer. Out of 40 people who show demonstrated interest, ten become customers. The close ratio is 25 percent.

Maybe there’s an internal process that could increase Moira’s close ratio, but other than recommending that human beings follow up with the non-subscribers, there’s little you can do about that. So the question to ponder is this: Is there something Moira can do in any of these situations to have a positive influence on either the number or the quality of people who use the software on the 30-day Free Trial?

Action points: In reality, this doesn’t seem to be the primary issue, but the fact is, sales increase when you attract more qualified people with demonstrated interest to perform a product demo. That’s probably going to happen farther upstream. I recommend examining the post-demo communications and CTRs for reattraction to see if Moira’s efforts to reattract are underperforming.

SQLs

Moira defines SQLs as people who have successfully completed a software demonstration with a sales consultant. Of the people who complete a sales demo, 50 percent move on to demonstrated interest by signing up for a free 30-day trial.

In this case, Moira researched the close ratios and 50 percent is a pretty darn good number for her industry. So, unless there is a reporting problem any inefficiency in the conversion chain is probably not from the SQL link, and marketing influence here may be limited anyway.

Action points: I advise Moira to check her marketing communications to see if improving any of the following would have a meaningful impact:

• Predemo engagement: Is Moira’s company sending automated meeting reminders to reduce no-shows? Is her marketing team creating content that asks plenty of qualifying questions prior to the software demonstration?
• Product demo: Has marketing looked at the presentation to ensure that it’s written in language that “speaks” to each target persona?
• Post-demo: Is she sending a workflow series of emails that are both reattractive for reengagement or encouragement for a sale?

MQLs

Moira defines her MQLs as individuals who have attended a webinar, completed a buyer survey, or filled out a “Contact Us” form. She also uses visitor onsite activities for lead scoring with a 100-point score elevating a lead to MQL status.

Big picture, 160 of the 500 total monthly leads are considered a MQL. Half of those connect with a salesperson for a product demo. That sounds good and it probably is, but Moira could test for improvements. Is there a big difference between the customer conversion paths taken by MQLs and SQLs?

Action points: I recommend looking at Moira’s lead scoring to see if perhaps more people should be designated SQLs rather than MQLs. Because this designation would increase the number of follow-up calls for her sales team, she’d need to make sure Sales has capacity to handle the new workload. Also, because a percentage of these leads may be incrementally harder to encourage, the close ratio from SQL would probably go down.

Modeling the respective conversion paths for MQLs and SQLs and navigating MQLs toward any distinct, differentiating SQL path onsite may increase the percentage of leads who schedule and perform a demo, which would positively affect Moira’s Demonstrated Interest and Customer numbers down the chain. Lastly, she should look at automated email messaging and consider A/B testing a promotional message with a CTA with an urgent deadline against the current CTA, in the hope of increasing demonstrated interest. (So, maybe a 60-day free trial for the first 10 people to schedule a demo?)

Leads

Moira defines inbound leads as website visitors who contacted the company via web phone calls (tracked by a unique number on her website), onsite e-book downloads, or other onsite form conversions like “Contact Us.”

Improving Moira’s CPL of $500 seems possible. To achieve a more efficient CPL, she might consider two alternatives; either increasing the quality of the leads or reducing the ad spend by analyzing where the 52 percent of unqualified traffic is sourcing.

Action points: Moira should review the content strategy to retool the target keyword list as a starting point that has implications for both SEO and PPC. She should compare performing and non-performing keywords, see what words are attracting the most unqualified leads, and remove them from her plan. She should examine the engagement content that her customers consume and navigate some of the less qualified (but not least qualified) traffic to those conversion pages to determine whether the quality of the page is causing conversion or if she’s simply attracting visitors who will never convert as a quality lead.

Visits

According to Moira’s Google Analytics, her website’s monthly traffic is 20,000, 50 percent of which were returning visitors and 50 percent new visitors. Unique visitors equals 10,000 people per month.

So what? Because Moira’s website attracts only 10,000 unique visitors per month (the other half are from people returning to the site one or more times), the conversion ratios are actually much higher than originally reported. In fact, they’re twice as good. It’s why I recommend using Unique Visitors as your baseline traffic numbers instead of overall traffic numbers. So, why did I use overall traffic in this example? To prove my point! It may not be as easy to increase your conversion ratios as it might first appear. Using flawed data to project future outcomes may end in disaster so beware the sources of your conversion metrics. In this case, use the number of unique visitors.

Action points: Moira has tremendous reattraction: 50 percent of her customers are returning to her site. Why isn’t the other half reconverting? You’ll always have unqualified traffic, sure, but I would look at the reattraction workflow campaigns, asking if the reconversion rate should be higher. If the answer is yes, she should take a look at the actual workflow, test the workflow and its components including email frequency and recency, CTAs, and reengagement content.

Impressions

Moira’s attraction marketing generates monthly traffic numbering 20,000 people each month, half of which are unique visitors. 10,000 visits are from people returning to the site.

Comparing the attraction sources and the amount invested into these initial attraction inputs and the amount invested and the resulting reattraction may suggest some answers to some important questions, including:

• Does the fact that 50 percent of visits were revisits signal that inbound remarketing and retargeting campaigns are performing well?

  or

• Does the fact that only 50 percent of her site’s visitors are new signal an inefficient initial attraction campaign?

Action points: Drilling deeper requires a CTR and a conversion ratio for the past month, and then comparing it to historical traffic and conversion data. Market anomalies, seasonality, or events may explain away spikes. I would particularly look at any reattraction, reaction, and reconversion campaigns to learn the source of the revisits. Lastly, checking the attraction source of the 50 percent of traffic designated as first time visitors, following those visitors down the conversion path, and segmenting them as buyers and non-buyers helps over-performing conversion sources. Identify those sources and invest more to see if you produce similar results.

Determining the value of your customer segments

Inbound marketers are as guilty as anyone else in the business world in compiling reams of meaningless data reports. Marketers tend to look at aggregate data, which explains the “what” but not the “what if,” or the “why.” Asking “what if” all along the customer purchase path results is the road to improved marketing and business outcomes. If you take nothing else away from this book, remember to ask “why” and “what if.” Answering the “why” with insightful solutions is rewarding and fun, I promise!

With that in mind: What if you segmented your data into more meaningful groups? Using Moira’s two customer groups as an example, let’s segment and analyze.

Customer Group A represents 90 percent of customers and 82 percent of revenues. Customer Group B represents 10 percent of customers and 18 percent of revenues.

Total revenues are $66,000 per month.

What if you replaced one customer from Group A with two from Group B?

Customer Group “A” now represents 80 percent of customers and 67 percent of revenues. Customer Group “B” now represents 20 percent of customers and 33 percent of revenues.

Total revenues are now $72,000 per month.

What if you replaced two customers from Group A with two from Group B?

Customer Group “A” now represents 70 percent of customers and 54 percent of revenues. Customer Group “B” now represents 20 percent of customers and 46 percent of revenues.

Total revenues are now $78,000 per month.

If you, as an inbound marketer, determine how to replace three valuable customers with three even more valuable customers, you increase your marketing efficiencies while increasing sales. Sounds like a winner to me.

But wait, there’s more. By replacing just two customers from one segment with another, you’ve also increased the LTV each month from $198,000 to $234,000, an increase of $36,000. Over the course of the next 12 months, you’ve just created enough customers to generate $432,000 in incremental revenue over the next three years!

Replicating successful conversion paths

Let’s keep this short. When you discover a successful conversion path for one segment, replicate the working parts by testing and applying your actionable findings to other product pyramids, inbound campaigns, and conversion paths.

Remember what my buddy, business partner, and inbound marketing expert, Nate Davidson says: “Do more of what works. Do less of what doesn’t.”