Measuring MQL to SQL conversion to determine marketing ROI can be challenging, as it’s very rare that a lead will pass through your funnel in one linear path. In our experience, this is more likely for software vendors than tech service companies, as the demo is often the key conversion point. It’s much more likely that leads will pass through a number of touchpoints at different stages in the buying process - typically 6 to 8 to convert a prospect.
First Touch Attribution
‘First Touch Attribution’ is often used to gauge marketing effectiveness, because it is easier to track and measure. ‘Multi-touch Attribution’ often requires analytical software or systems such as Bizible or Engagio. First touch attribution varies considerably, based on the lead source. Some benchmarks are shown below:
|
Original lead source (First touch attribution) |
ROMI Clients (Average) | Geckoboard |
|
Customer referral |
55% |
24.7% |
|
Webinars |
21% |
17.8% |
|
Events |
10% |
4.2% |
|
Telemarketing (Cold prospecting) |
5% |
No data |
|
Guides (Whitepapers/eBooks) |
7% |
3% |
|
|
2% |
1% |
|
Social (Linked-In) |
3% |
No data |
|
SEO/PPC |
2% |
No data |
Marketing Customer Acquisition Cost (MCAC)
MCAC is a good indicator of marketing effectiveness as it identifies the average cost attributed to marketing when acquiring a new customer. MCAC is calculated as:
MCAC = Total Life Time Value (LTV) of new customers acquired / Total new business marketing costs
MCAC benchmarks are difficult because it all depends on your average LTV and the amount of marketing intervention required to win a new customer. First ask, is marketing just generating raw leads or heavily involved in supporting sales and generating the vast majority of opportunities? Then ask, are the total new business marketing costs in line with this level of contribution?
Let’s say new business marketing costs are 30% of the overall Total Customer Acquisition Costs (CAC), which includes sales costs. CAC is generally benchmarked at LTV: CAC of 3:1. So your LTV should be at least 3 times your CAC.
If marketing costs are 30% of the CAC process then your MCAC ratio would be 10:1, shown in average deal terms below:
Average LTV £30,000 Average CAC £10,000 Average MCAC £3,000
The way to then assess marketing effectiveness is to analyse how much marketing is contributing to winning new business. For example, this could be decided by quantifying its contribution to the number of first-touch marketing-generated opportunities in the pipeline or marketing’s level of sales enablement.
If you’re MCAC ratio is low, say 5:1, and marketing’s contribution is also viewed as low, then it’s likely you are spending too much on marketing. Ideally, you want your MCAC ratio to be higher (i.e. lower spend) and it’s contribution to be higher to achieve a good ROMI (Return on Marketing Investment).
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Remedies for improving lead conversion
There are many opportunities to improve MQL to SQL conversion but below are the most obvious:
- Sales cycle length: A longer sales cycle length is going to change the window that you need to look at when calculating your conversion rate. If your typical sales cycle lasts many months, then calculating MQL to SQL conversion rates within the last month isn’t going to give you much insight. Keeping your sales cycle length in mind when assessing your conversion process is key, as you may ignore dormant MQLs that could soon turn to SQLs.
- Focus on the best lead sources: You’ll quickly find that leads from different sources convert at very different rates. For instance, the conversion rate for referral leads are usually quite high, while a lead that comes in through a webinar will be of lower quality. In this case, investing in a formal referral programme may yield better results. Understanding where your best leads come from can help you to focus on the leads that are most likely to become buyers and improve your MQL to SQL conversion rates.
- Understand your buyer journey: Research into the path your buyers take, their information needs and preferences at each stage, alongside an honest assessment of your current gaps, can dramatically improve conversion rates. For example, with an SaaS company we work with, we discovered that monthly payments was a key preference for buyers, yet the company clearly indicated on their website they would accept annual payments only. This subtle change to monthly payments has led to a 7% increase in demo requests.
- Sales/marketing and system alignment: Good MQL to SQL conversion relies on close alignment between marketing and sales. Definitions and criteria need to be universally agreed and expectations set. The hand off process needs to be carefully thought through and systems need to automate this process to ensure sales productivity. The common problem we see is where leads are passed to sales too early, which results in sales people regarding MQLs in general as a waste of their time. A good process and clear alignment will reduce this friction.
- Slow and inappropriate follow-up: Often the lag time for sales to follow-up MQLs is too slow. Potential buyers won’t remember whose website or event pod they visited days after the event, which means you’ve lost the opportunity to leverage the engagement. Follow-up needs to match the stage the buyer is at in their process and sales people need to treat them in the right way – no point in pitching your services to someone who has just attended your webinar. But it is a great way to start an engagement and begin nurturing a good fit prospect.
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