When marketing towards the bottom of the funnel, our core goal is to generate conversions. We often think of conversions as sales or leads generated, but conversions can come in many forms. So-called ‘micro-conversions’ that indicate user interest may include:
- Email subscriptions (including for out-of-stock products, etc)
- Free trial or demo product take-ups
- Specific video views
- Viewing a product pricing page
- Product add-to-carts
- An eBook, whitepaper, or case study download
With that in mind, how should we be tracking, measuring and optimising towards not only conversions and conversion volume, but crucial lower funnel metrics?
Identify the right metrics for your brand
The first — and most crucial — step is to uncover what the right metrics are to be tracking. This sounds simple, but you’d be surprised how many marketers and business owners slip up here, as it’s easy to get distracted.
For example, a conversion-driving campaign may have a strong CTR or engagement rate. That’s great! But if it’s followed up with a weak or non-existent conversion rate, and your goal is to drive conversions, that makes the ad or campaign less effective. By focusing on the metrics that matter for lower funnel activity, we can remain focused on what really matters: conversions.
So, what metrics should we be optimising towards?
B2B lower funnel metrics
Here are a few metrics to consider. Remember, B2B brands may experience long sales cycles and have a focus on nurturing prospects ahead of eventual lead generation.
CAC = Customer Acquisition Cost. Put simply, this is the average cost it takes to acquire one customer. CAC differs from CPA (Cost per Acquisition), because it includes the full cost of all marketing and sales investment, not just that of marketing. For the most benefit and the highest return, you’ll want this metric to be as low as possible. Calculate your CAC by first adding up the total cost of your sales and marketing spend over a period of time, and then dividing this figure by the number of customers acquired over that same period.
CPL = Cost Per Lead. (A quick disclaimer here is that the definitions of CPL and CPA may differ per company and are sometimes used interchangeably. So make sure that you, your sales team and your leadership teams are aligned on what your core metric is and what it means.) It’s also important to remember that a lead doesn’t always mean a sale. A lead could be someone who has completed one of the micro-conversions listed above.
CPL is simply calculated by calculating the marketing budget spent over a period and dividing this by the number of leads generated over that same period. While you can — and should — calculate overall CPL for your business, this can be calculated by platform too; you’re likely to see CPLs differ between platforms and campaign types.
CPA = Cost Per Acquisition. Similarly to CPL, CPA is the average cost per acquisition or sale: what does it cost to generate a paying customer? Calculate CPA by calculating the marketing budget spent over a period of time, and dividing this by the number of paying customers generated. Your aim should be to make both CPL and CPA as budget-efficient as possible, in order to get as many conversions as you can from your budget.
MQL Volume = Marketing Qualified Lead Volume. Often within B2B marketing, your goal will be to generate marketing-qualified leads (MQLs) which are then nurtured into sales-qualified leads or SQLS.
However, it’s easy to get distracted by a strong MQL volume. While volume is important, quality is too. And, more often than not, it’s better to generate a lower volume of highly qualified and relevant MQLs than a stronger volume of unqualified leads.
MQL to SQL rate = Marketing Qualified Lead to Sales Qualified Lead rate.
Calculate this by taking the total number of MQLs generated over a period, and dividing this by the number of those that turned into SQLs. Then, multiply this number by 100 to find your MQL to SQL conversion rate. For example, if you generated 1,000 MQLs over a period and 100 of those turned into SQLs, your rate would be 10%: [(1,000/100)*100] = 10%.
One significant factor that may skew this is when B2B brands have long sales cycles. An MQL generated in January could turn into an SQL in 3, 6, or 9 months. So, calculating your MQL to SQL conversion rate over a single month may generate a warped view. If your average sales cycle is six months, for example, it’s best to use the MQLs generated six or seven months ago to calculate your MQL to SQL rate for the current month.
B2C lower funnel metrics
For B2C brands, the core focus is generally on prioritising volume, as well as repeat purchases or promoting opportunities for cross-selling or up-selling.
AOV (Average Order Value). The average amount that a single order generates in revenue (not profit). Calculate AOV over a set period by dividing the total revenue generated by the number of orders received. For example, 1,000 orders in a calendar month generating £100,000 in revenue would deliver an AOV of £100. Of course, you’ll want to increase and maximise your AOV — this can be done by prioritising higher-value products in your advertising efforts.
CLTV (Customer Lifetime Value). How much, on average, a customer is ‘worth’ to your brand during their relationship with you. To calculate CLTV, multiply the AOV of an average customer by the average number of orders a single customer makes with you. (For example, an AOV of £100 with an average of four orders over three years will generate a CLTV of £400).
While one-off orders and driving volume is great, the real value is in creating a longer term customer relationship with regular, repeat business. This is even better if each subsequent order is generated organically or from automated email campaigns, rather than by paid efforts each and every time, which will reduce your return on each customer.
By focusing your marketing efforts on maximising CLTV, you’ll have breathing space to spend a little more upfront on customer acquisition. Instead of focusing only on the cost incurred to generate one order, sale, or lead, you can use CLTV to understand better the full cost of generating all orders by an average customer. This will improve your ROI and ROAS.
Units Sold. Obvious? Yes. However, effective B2C marketing often comes down to volume. Luckily, this is easily calculated through your CMS or shopping analytics. If you’re able to create a baseline of ‘normal’ performance outside of marketing, or ahead of a large-scale advertising campaign, this will help you to prove the value of marketing should your attribution be lacking.
ROAS = Return on Ad Spend. Finally, ROAS. ROAS is calculated simply by dividing the total revenue generated by a campaign by the total spend on the campaign over the same period. ROI (Return on Investment) calculations generally include all expenditures outside of just the marketing spend incurred — such as tools, software, team salaries, etc. Instead, ROAS offers a much clearer indication of the return generated from ad spend only. A strong benchmark for this — although of course, it varies by location, industry, product cost, etc — is 4:1.
How to accurately measure your core metrics
Once you have found the most relevant metrics to track for your lower funnel activity, you’ll need to create three things:
- A SSOT (Single Source of Truth)
- A regular reporting cadence
- Data benchmarks
A SSOT (Single Source of Truth)
A SSOT is a single, central resource where all data is stored, analysed and collected. SSOTs should be accurate, accessible, consistent and reliable, and that means that they can be used by everyone in a team and will contribute to better data-driven decision-making.
An effective SSOT could be your central web analytics tool (the accuracy of this can be improved by using auto-tagging and UTMs on all traffic sources), a central tool such as CM360, or by using integrated sales and marketing software such as HubSpot.
All analytics and reporting tools have their attribution and measurement quirks — but by using a SSOT across an entire business, these are at least applicable to all reports.
A regular reporting cadence
The frequency and data delay will also depend on what campaign types you’re reporting on. For example, it’s generally considered sensible to wait 24–48 hours after sending an email campaign to effectively gauge open rates and engagement, etc. For PPC and paid social campaigns, it can take a few days to finalise and reconcile data — removing click fraud, inaccurate click data, and updating conversion attribution. Some SSOTs such as GA4 take several hours to update (excluding real-time reporting etc.). But, as with a SSOT, keep any reporting delays consistent. If you want to report on weekly performance every Monday, make sure it’s done every Monday — and not sometimes on a Tuesday or Thursday.
Take baseline metrics
Ahead of any new campaigns or mass shifts in budgets or targeting, it’s important to create baseline metrics to report from. This will help you to properly measure the impact of your campaigns and ads.
By using a SSOT with a regular reporting cadence, you can be sure that any measurements you take are accurate.
