Metrics that matter: what a consumer VC looks for in a start-up’s numbers
Spoiler alert: all metrics matter. They help build a rich tapestry of the company’s health today and in future. In this blog, I explain why, and what all these metrics are.
There are a number of good overviews out there on the B2C metrics that VCs look for. Ones to check out come from 500 Global, Octopus Ventures and Icebreaker VC. I’m a particular fan of Octopus’s offering (Matt Chandler — 👏) and their framework of the ‘power train’ and ‘fast’ vs. ‘slow’ commerce.
However, these overviews have limited utility for founders. Why? Firstly, some of them suggest that each VC applies a unique approach or formula to spit out a binary yes / no answer on whether the metrics make the grade or not. Secondly, and this applies to all the articles mentioned above, they are far from exhaustive.
Having spent some time refreshing and codifying our approach to metrics over the past couple of months, my unerring conclusion is that we (dmg ventures) need to be capturing as many data points as possible and assessing each company on a case-by-case basis, whilst doing some sense checking against benchmarks. My belief is that every VC is doing something similar. If there is a VC reading this with a magic metric formula which will help me ‘get rich quick’, please get in touch…
My job as a VC is to build confidence out of obscurity and complexity. The more data points I can capture to build a holistic view of a company, the better. It also gives us a richer comparative data set when looking at other companies in future. As a start-up is a moving feast, these data points help gauge performance today and allude to what performance might be like in future.
In my previous role at InPost, I spent a significant amount of time building out our metric framework in the UK, and am all too familiar with how complex it can be. By sharing a fairly exhaustive list of metrics which an investor might look at, I hope to make your life a little easier as you construct your framework. As mentioned above, these metrics are relevant to B2C companies but are relatively sector-agnostic within that. There will be a bunch of sector-specific metrics relevant to your industry which you should also consider incorporating.
🌳 Building a metric master and a KPI tree
A ‘metric’ is subtly different from a ‘KPI’. While KPIs measure progress toward specific goals, metrics are measurements of overall business health. In practice, the two are often used interchangeably.
However, I recommend keeping the two distinct and creating a structure around both.
Enter, the ‘metric master’ and ‘KPI tree’.
In a perfect world, a metric master is a dashboard which tracks every metric pertinent to your business, taking on the role of a company’s brain. It should be used by the founders and other relevant team members to monitor the minutiae of the day-to-day operations of the business. The metric master should delineate leading and lagging indicators, which helps inform how to respond when the metrics move in a given direction.
The KPI tree draws a subset of metrics from the metric master to tell a coherent narrative (to potential investors and employees) around current business objectives. It is likely to evolve as business priorities change.
A KPI tree is akin to a complex, living organism. It should be made up of a number of interrelated layers, with the layers increasing in their importance until you reach two of three critical KPIs at the top, which are, in turn, driven by the layers beneath. Though the KPI tree highlights some metrics more than others, all the metrics captured are interdependent and important in their own way.
Setting up a metric master and KPI tree is one of the first things you should do when launching a new start-up. Doing this enables you to build a business with data at its heart.
Tracking a wide range of metrics is useful for a variety of reasons. It helps teams figure out what’s going right and wrong, and gives clues on how to address them. Tracking these metrics can also be used to keep teams engaged and motivated, through sharing the KPI tree regularly, and appease data-hungry investors. KPIs, in particular, also instill focus, often a big issue with start-ups which can easily be pulled in every direction.
Building a metric framework early on puts you on the front foot with investors. It enables you to finesse a compelling story over time, backed up by data (e.g., you decided to implement this product pivot because of the performance of a certain metric). A data-backed strategy gives investors a huge amount of comfort.
📈 The metrics dmg ventures looks at
Below, I delve into the specific metrics we aim to capture as part of our due diligence process. Not every company will have every metric to hand and we won’t ask every company for every metric, but the more we can capture, the better. We have a separate comparative framework for three business models which cover our investment strategy within the consumer space; commerce (companies directly selling products and services), freemium (free-to-use apps with a paid-for, premium subscription option) and marketplaces (an intermediary for buyers and sellers of a given product or service). For commerce and marketplaces, we also divide companies into ‘fast’ (purchases at <1 month frequency) and ‘slow’ (purchases at >1 month frequency) buckets for benchmarking purposes. There’s also the ad-based or data-based model (e.g., Facebook), but we don’t tend to look at this type of company at dmg ventures.
Internally, we have a defined calculation for each metric and a specific time period during which we measure the metric, to ensure consistency when we’re comparing different companies. We also have standardised definitions for terms like ‘active customer’, ‘user’ and ‘activation’. Finally, as a rule of thumb, we consider all metrics net of VAT.
Simplistically, the success of a company boils down to customer acquisition, customer retention and cost control. The metrics detailed below all relate to one or more of these tenets.
As mentioned above, there will also be a ton of sector-specific metrics not captured here, which you should augment into your metric framework. The benchmark levels for each metric can also differ wildly by sector.
Finally, it’s important to note that the first metrics we look at relate to whether the start-up in question aligns with dmg ventures’ investment strategy and where we can add value. These metrics are tailored to us.
❗❗❗ The metrics that REALLY matter
Despite start-ups’ heterogeneity, there are a couple of metrics which are vital to all (and yes, you could argue for other metrics to be included here):
- LTV / CAC (lifetime value / customer acquisition cost) — the contribution margin made per customer over that customer’s lifetime vs. the marketing cost of acquiring the customer. The acid test of whether a company is, or can ever be, profitable
- TrustPilot rating — a temperature check of customer satisfaction
🛒 Commerce metric master
- dmg ventures fit 🤝
- % of population addressable — the proportion of the population the product or service is relevant for. Though a consumer start-up should have a beach head consumer demographic, where we can add value is with companies that have mass market appeal
- % female customers — a number of dmg media’s publications have a strong female skew, meaning we look for companies which over-index here
- % 25–45-year-old customers — an audience where we have strong reach through MailOnline
- % 50+-year-old customers — a strong fit with Daily Mail’s readership
- % UK customers — where dmg media reaches the majority of the population every month
- % US customers — where MailOnline reaches 65m readers per month
2. Sales channel ⬆️
- % direct-to-consumer
- % retail
- % marketplace
- % other
3. Marketing efficiency 💷
Total customer base:
- ROAS (revenue) — revenue / marketing spend. Typically, aiming for 2x / 3x or more, and trending upwards
- ROAS (contribution) — contribution margin / marketing spend. Looking for 1x or more, and trending upwards
- Spend, revenue and ROAS for each customer acquisition channel — looking for signs that each customer acquisition channel can scale
- % marketing spend on below the line channels
- % marketing spend on above the line channels — interesting for us to see how much a company has tested above the line campaigns previously
- Instragam / TikTok / Facebook followers and size of mailing list— is the brand building an engaged community?
- Website unique visitors and aggregate visitors
- Website conversion — web orders / web visitors
- Cart abandonment — (baskets created minus web orders) / baskets created
New customer base:
- New customer ROAS (revenue) — new customer revenue / new customer marketing spend
- New customer ROAS (contribution) — new customer contribution margin / new customer marketing spend
- Blended CAC — new customer marketing spend / number of new customers
- Paid CAC — new customer marketing spend / number of new customers acquired through non-organic channels
- % new users acquired organically
- K factor — new referred customers / existing users. A metric used to assess a start-up’s viral potential
Repeat customer base:
- Existing customer ROAS (revenue) — existing customer revenue / existing customer marketing spend
- Existing customer ROAS (contribution) — existing customer contribution margin / existing customer marketing spend
- Blended customer retention cost — existing customer marketing spend / existing active customers
4. Subscriptions 🎫
- # new subscribers
- % subscription customers — total active subscribers / total active customers
- % subscription revenue — subscription revenue / total revenue
- % signed up to <1/1–3/ 3+ month subscription
- % signed up to premium / average / basic subscription
- % month-on-month increase in average subscription price
- Gross monthly retention — number of current month existing subscribers / previous month subscribers
- Net monthly retention — current month existing subscriber revenue / previous month subscription revenue
5. Total customers 🧘
- Total active customers
- Lifetime customers — unique customers who have bought a product or service since inception
- % active customers — active customers / lifetime customers
- # orders
- Orders per customer
- AOV — revenue / orders
- Items per basket
- Product return rate — returns / orders
- Revenue
- Revenue per customer
- Revenue compound monthly growth rate
- Customer service response time — average time to respond to customer query
- NPS (net promoter score)
- Average TrustPilot rating
- # TrustPilot reviews
- % of TrustPilot 1* and 2* ratings
6. New customers 🤸
- New active customers
- % new customers — new customers / total active customers
- New customer AOV — new customer spend / new customer orders
- Items per basket
- New customer revenue
7. Existing customers 🙌
- Existing active customers
- Existing customer AOV — existing customer spend / existing customer orders
- Revenue per existing customer — existing customer revenue / existing active customers
- Existing customer revenue
- Month 1/3/6/12 cumulative # purchases per customer
- Month 1/3/6/12 cumulative revenue per customer / first order revenue
- Month 3/6/12 spend per active customer vs. month 1 spend per customer
- Month 3/6/12 gross retention % — month 3/6/12 active customers / month 1 customers
- Month 3/6/12 net retention % — month 3/6/12 cohort revenue / month 1 cohort revenue
- Existing customer revenue retention — current month existing customer revenue / last month revenue
8. Retail 🏪
- # doors
- Units sold per store per week
- Revenue per store per week
- Same store sales growth — current month revenue from stores open 1 year ago / store revenue 1 year ago
9. Operational efficiency ⚙️
- # SKUs
- D2C/retail/marketplace gross margin
- D2C/retail/marketplace contribution margin
- Logistics / revenue — total logistics cost / total revenue
- Overheads
- Overheads / revenue — total overheads / total revenue
- Gross burn — total costs
- Net burn — EOP cash minus BOP cash
- Burn multiple — net burn / net new revenue. An in-vogue metric more relevant for B2B start-ups
- Customer service contact rate — customers contacting customer service / total active customers
- Customer service time spent per query
10. Customer economics 🧮
- LTV — ((1 / Existing customer revenue retention %) / 2) * monthly contribution per customer. Frequently miscalculated so take note! People often either use revenue rather than contribution, or do not divide 1 / retention by 2 to get average lifetime
- LTV / CAC
- 1st order contribution / CAC — (1st order revenue — 1st order direct costs) / CAC. Looking for a ratio of >1 to signal that CAC is paid back or more on the first order
- Payback period — the number of months it takes to pay back the CAC
- 2x payback period — the number of months it takes to pay back 2x CAC
🛒 Freemium metric master
- dmg ventures fit 🤝
- % of population addressable — the proportion of the population the product or service is relevant for. Though a consumer start-up should have a beach head consumer demographic, where we can add value is with companies that have mass market appeal
- % female customers — a number of dmg media’s publications have a strong female skew, meaning we look for companies which over-index here
- % 25–45-year-old customers — an audience where we have strong reach through MailOnline
- % 50+-year-old customers — a strong fit with Daily Mail’s readership
- % UK customers — where dmg media reaches the majority of the population every month
- % US customers — where MailOnline reaches 65m readers per month
2. Marketing efficiency 💷
Total customer base:
- ROAS (revenue) — revenue / marketing spend. Typically, aiming for 2x / 3x or more, and trending upwards
- ROAS (contribution) — contribution margin / marketing spend. Looking for 1x or more, and trending upwards
- Spend, revenue and ROAS for each customer acquisition channel — looking for signs that each customer acquisition channel can scale
- % marketing spend on below the line channels
- % marketing spend on above the line channels — interesting for us to see how much a company has tested above the line campaigns previously
- Instragam / TikTok / Facebook followers and size of mailing list — is the brand building an engaged community?
- Website unique visitors and aggregate visitors
User base:
- Download CAC — new customer marketing spend / new downloads
- New user CAC — new customer marketing spend / new activated users
New customer base:
- New customer ROAS (revenue) — new customer revenue / new customer marketing spend
- New customer ROAS (contribution) — new customer contribution margin / new customer marketing spend
- Blended CAC — new customer marketing spend / number of new customers
- Paid CAC — new customer marketing spend / number of new customers acquired through non-organic channels
- % new users acquired organically
- K factor — new referred customers / existing users. A metric used to assess a start-up’s viral potential
Repeat customer base:
- Existing customer ROAS (revenue) — existing customer revenue / existing customer marketing spend
- Existing customer ROAS (contribution) — existing customer contribution margin / existing customer marketing spend
- Blended customer retention cost — existing customer marketing spend / existing active customers
3. Users
- Lifetime and new downloads
- Lifetime and new activations
- Activation rate — lifetime activations / lifetime downloads
- New trials
- Activation-trial conversion — new trials / new activations
- Trial-subscription conversion — new subscriptions / new trials
- Download-subscription conversion — New subscriptions / new downloads
- Activation-subscription conversion — new subscriptions / new activations
- Month 1/3/6/12 user retention
- DAU
- WAU
- MAU
- DAU / WAU
- WAU / MAU
- MAU / downloads — MAU / lifetime downloads
4. Subscriptions 🎫
- # new subscribers
- % subscription customers — total active subscribers / total active customers
- % subscription revenue — subscription revenue / total revenue
- % signed up to <1/1–3/3+ month subscription
- % signed up to premium/average/basic subscription
- % month-on-month increase in average subscription price
- Gross monthly retention — number of current month existing subscribers / previous month subscribers
- Net monthly retention — current month existing subscriber revenue / previous month subscription revenue
5. Total customers 🧘
- Total active customers
- % active customers — active customers / lifetime customers
- # orders
- Orders per customer
- AOV — revenue / orders
- Items per basket
- Revenue
- Revenue per customer
- Revenue compound monthly growth rate
6. New customers 🤸
- New active customers
- % new customers — new customers / total active customers
- New customer AOV — new customer spend / new customer orders
- Items per basket
- New customer revenue
7. Existing customers 🙌
- Existing active customers
- Existing customer AOV — existing customer spend / existing customer orders
- Revenue per existing customer — existing customer revenue / existing active customers
- Existing customer revenue
- Month 1/3/6/12 cumulative # purchases per customer
- Month 1/3/6/12 cumulative revenue per customer / first order revenue
- Month 3/6/12 spend per active customer vs. month 1 spend per active customer
- Month 3/6/12 gross retention % — month 3/6/12 active customers / month 1 customers
- Month 3/6/12 net retention % — month 3/6/12 cohort revenue / month 1 cohort revenue
- Existing customer revenue retention — current month existing customer revenue / last month revenue
- Customer service response time — average time to respond to customer query
- NPS
- Average TrustPilot rating
- # TrustPilot reviews
- % of TrustPilot 1* and 2* ratings
8. Operational efficiency ⚙️
- Gross margin
- Contribution margin
- Overheads
- Overheads / revenue — total overheads / total revenue
- Gross burn — total costs
- Net burn — EOP cash minus BOP cash
- Burn multiple — net burn / net new revenue. An in-vogue metric more relevant for B2B start-ups
- Customer service contact rate — customers contacting customer service / total active customers
- Customer service time spent per query
9. Customer economics 🧮
- LTV — ((1 / Existing customer revenue retention %) / 2) * monthly contribution per customer. Frequently miscalculated so take note! People often either use revenue rather than contribution, or do not divide 1 / retention by 2 to get average lifetime
- LTV / CAC
- 1st order contribution / CAC — (1st order revenue — 1st order direct costs) / CAC. Looking for a ratio of >1 to signal that CAC is paid back or more on the first order
- Payback period — the number of months it takes to pay back the CAC
- 2x payback period — the number of months it takes to pay back 2x CAC
🏛️ Marketplace metric master
- dmg ventures fit 🤝
- % of population addressable — the proportion of the population the product or service is relevant for. Though a consumer start-up should have a beach head consumer demographic, where we can add value is with companies that have mass market appeal
- % female customers — a number of dmg media’s publications have a strong female skew, meaning we look for companies which over-index here
- % 25–45-year-old customers — an audience where we have strong reach through MailOnline
- % 50+-year-old customers — a strong fit with Daily Mail’s readership
- % UK customers — where dmg media reaches the majority of the population every month
- % US customers — where MailOnline reaches 65m readers per month
2. Marketing efficiency 💷
Total:
- ROAS (revenue) — revenue / marketing spend. Typically, aiming for 2x / 3x or more, and trending upwards
- ROAS (contribution) — contribution margin / marketing spend. Looking for 1x or more, and trending upwards
- Spend, revenue and ROAS for each customer acquisition channel — looking for signs that each customer acquisition channel can scale
- % marketing spend on below the line channels
- % marketing spend on above the line channels — interesting for us to see how much a company has tested above the line campaigns previously
- Instragam / TikTok / Facebook followers and size of mailing list — is the brand building an engaged community?
- Website unique visitors and aggregate visitors
Sellers
- Blended seller CAC — seller marketing spend / new sellers
- Paid seller CAC — seller marketing spend / new sellers acquired via non-organic channels
- % new sellers acquired organically
- % new sellers who were buyers
- K factor — new referred sellers / existing sellers
- Website conversion (seller) — seller postings / web visitors
- Cart abandonment (seller) — (seller postings started — seller postings) / seller postings started
Buyers
- Blended buyer CAC — buyer marketing spend / new buyers
- Paid buyer CAC — buyer marketing spend / new buyers acquired via non-organic channels
- % new buyers acquired organically
- % new buyers who were sellers
- K factor — new referred buyers / existing buyers
- Website conversion (buyer) — buyer purchases / web visitors
- Cart abandonment (buyer) — (baskets created — buyer purchases) / baskets created
3. Transactions 💸
- # bookings — bookings made but not necessarily filled
- # transactions
- % fulfilled bookings — transactions / bookings
- GMV
- AOV
- Take rate — revenue / GMV
- Revenue
- Sell through % — transactions / listings
- Sell through average time — date of sale minus date of listing (average)
4. Sellers 🛍️
- Lifetime seller registrations
- Lifetime seller activations
- Activation rate — lifetime seller activations / lifetime seller registrations
- # lifetime attempted sellers
- # lifetime sellers
- Seller / attempted seller
- # active sellers
- # new active sellers
- Active seller % — active sellers / lifetime sellers
- % of sellers who are also buyers — # lifetime sellers (who are also buyers) / # lifetime sellers
- Listings per active seller
- Listings per active seller (who is also a buyer) — listings (from sellers who are also buyers) / active sellers (who are also buyers)
- Month 1/3/6/12 listing frequency per active seller — month 1/3/6/12 listings / month 1/3/6/12 active sellers
- Month 3/6/12 seller gross retention — month 3/6/12 active sellers / month 1 sellers
- Month 3/6/12 seller net retention — month 3/6/12 cohort listings value / month 1 cohort listings value
5. Buyers
- Lifetime buyer registrations
- Lifetime buyer activations
- Activation rate — lifetime buyer activations / lifetime buyer registrations
- Lifetime buyers
- # active buyers
- # new active buyers
- Active buyer % — active buyers / lifetime buyers
- % of buyers who are also sellers — lifetime buyers (who are also sellers) / lifetime buyers
- New buyer AOV
- Existing buyer AOV
- Month 1/3/6/12 cumulative purchases per buyer
- Month 1/3/6/12 cumulative GMV vs. first purchase — aggregate GMV per buyer to end of month 1/3/6/12 / initial order value
- Month 3/6/12 active buyer spend vs. month 1 active buyer spend — month 3/6/12 active buyer spend / month 1 active buyer spend
- Month 3/6/12 buyer gross retention % — month 3/6/12 active buyers / month 1 active buyers
- Month 3/6/12 buyer net retention % — month 3/6/12 cohort GMV / month 1 cohort GMV
- Customer service response time
- NPS
- Average TrustPilot rating
- # TrustPilot reviews
- % of TrustPilot 1* and 2* ratings
6. Operational efficiency
- Gross margin
- Contribution margin
- Logistics / revenue — total logistics cost / total revenue
- Overheads
- Overheads / revenue — total overheads / total revenue
- Gross burn — total costs
- Net burn — EOP cash minus BOP cash
- Burn multiple — net burn / net new revenue. An in-vogue metric more relevant for B2B start-ups
- Customer service contact rate — customers contacting customer service / total active customers
- Customer service time spent per query
7. Customer economics 🧮
- LTV — ((1 / Existing customer revenue retention %) / 2) * monthly contribution per customer. Frequently miscalculated so take note! People often either use revenue rather than contribution, or do not divide 1 / retention by 2 to get average lifetime
- LTV / CAC
- 1st order contribution / CAC — (1st order revenue — 1st order direct costs) / CAC. Looking for a ratio of >1 to signal that CAC is paid back or more on the first order
- Payback period — the number of months it takes to pay back the CAC
- 2x payback period — the number of months it takes to pay back 2x CAC
If you’ve made it this far, bravo! 👏 I realise this isn’t the lightest read you’ll come across. What it is intended to do is to give you an exhaustive lay of the land when it comes to sector-agnostic metrics a VC might look at.
Broadly, my advice is to set up a metric master and KPI tree as soon as possible, to ensure you can make fast, data-driven decisions and to keep team members and investors engaged. Map out all the pertinent metrics for your business in the metric master before crafting a narrative based around current business objectives with the KPI tree.
Best of luck!
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