How do you calculate your customer acquisition cost for different channels?

Customer acquisition channels are the methods through which a business attracts and converts new customers. These channels serve as touchpoints between the business and potential customers, helping to create awareness, generate interest, and ultimately drive sales. Offline and Online Channel examples: ? Direct Mail: Sending physical marketing materials to a highly targeted, model audience of potential customers. This is one of, if not the very best overall customer acquisition channels ? SEO: Optimizing website content to rank higher in search engine results pages (SERPs). ? PPC: Paid ads that appear on search engine results pages or social media platforms. ? Email Marketing: Sending targeted emails to nurture leads and drive conversions.

There are only two scalable acquisition channels for mass B2C products: Meta and Google. There are nuances with different programmatic platforms, there are niche cases with TikTok, but there are no other scalable channels. The key points: - For large mainstream B2C products and services, the two dominant paid advertising channels that can drive user acquisition at scale are Meta (Facebook, Instagram) and Google (Search, YouTube, Display Network). - Other programmatic ad platforms may offer additional targeting capabilities or niche reach, but cannot match the same scale. - No other digital advertising channels currently provide the same scalable reach and volume when launching and growing a mass consumer product.

It's worth remembering the offline channels - like television (both linear and CTV), direct mail, radio, and offline - also exist and can be quite usable and scalable for consumers and SMBs. (After all, people built great businesses before the internet ever existed.) With appropriate tracking, these can have great ROIs, as well as drive demand back into digital channels (eg brand search).

At our e-grocery, we do not use the concept of CAC. Instead, we calculate the cost of acquiring a user in three dimensions for each channel and cohort: - CPI: The cost to get a user to download our app; - CPA: The cost for a user to make their first purchase or place an order in our app; - Retention to third order: The percentage of users that make a third purchase after their initial order. This leads to different dynamics: - On Meta, CPI is very low but conversion rate is so low that CPA is higher than Google; - On Google, CPA is the lowest compared to Meta, but retention to third order is lower than for users from programmatic channels.

It’s difficult to calculate CAC per channel accurately. A user has many TP before buying and you must make estimate the weight of each channel. A lot of “guesswork”, especially with a complex marketing mix. Your attribution (CAC per channel) is only as good as your assumptions. Common mistakes: - Not considering time lags (future & past effects of marketing) - Giving digital channels & BOF too much weight - Considering total acquisitions per channel when e.g. campaign spent is adjusted One way to solve this are “channel tests” (switching channels on and off) to better understand incrementality. Or asking users how they came across your brand (do users remember and can make accurate statements?) Keep in mind, CAC per channel is a proxy.

In simple terms, one can calculate the customer acquisition cost by dividing all the costs spent on acquiring more customers (marketing, advertising and promotions) by the number of customers you acquire. For example, if a company spends $1000 on marketing annually and acquires 1000 customers in the same year, its CAC is $10.00.

In order for CAC to be a useful metric, it is critical that recurring customer orders are separated from new customer orders. Seems simple but we see it constantly - acquisition costs divided by all orders over a period of time is not CAC.

Calculating CAC for each marketing channel is tricky because a customer usually interacts with many touchpoints (TP) before making a purchase, and you need to guess how important each channel was in their decision. This involves a lot of estimation, which can be even more challenging with a complex marketing mix. Your ability to figure out the CAC for each channel depends heavily on how accurate your guesses are. Problem with attribution models: - Not considering time lags (future & past effects of marketing) - Giving digital channels & BOF too much weight - Considering total acquisitions per channel when e.g. campaign spent is adjusted Remember, calculating and comparing CAC by channel is an approximation and should be treated as such.

In my experience, acquisition channel is one of the dominant determinants of downstream customer behavior - everything from churn to customer value to behavior within the product. While CAC can be easy to measure, it's important to look beyond CAC to CLV and behavior downstream. To steal a line from Charlie Munger, you can "Pay good prices for fair customers, or fair prices for good customers." In my experience, the latter works much better (and finds you with much better relationships with everyone involved.)

To optimize CAC across different channels, we utilise the following types of creative analysis: - Creative content based on images - Creative colors - Headlines in creatives - Call-to-action - Language In more detail: - We test different images and visual content within our creatives to see which resonate best. - We experiment with different dominant colors in creatives to determine if certain palettes outperform others. - We iterate on ad headlines and messaging to optimise click-through rate. - We A/B test different calls-to-action within creatives to drive more conversions. - We tailor creatives for different languages and localisation.

The best way to optimize channel CAC is to stop using the parts of the channel that don't work. So mail fewer names (the less responsive ones), run fewer placements, bid on fewer keywords, and just pull back a little. After that, experimenting with offers can make a big deal - it's unlikely your customers don't understand your ad, so asking "how can I make my offering my compelling" vs "what color should this button be" can be a more effective approach.

This is cynical, but keep in mind that the most direct way to improve CAC is stop investing in the channel. This will immediately improve CAC and due to time lags you will still see acquisitions coming in! The point I am trying to make: CAC improvements are a long game and you should not over-emphasize on short term changes. This can be misleading because as soon as you invest in a channel, your CAC MUST increase because some effects are delayed (that’s just how it is, google PPC might be the only exception). Overall, marketers should focus more on channel effectiveness i.e. is the channel effective in increasing sales, before worrying about efficiency i.e. how expensive is it to acquire a customer.

It's key to look at CAC per channel & attribution with a critical eye. Naturally, attribution models will put higher weight on digital channels and BOF (bottom of the funnel). The risk: If you adjust your marketing-mix strictly based on the outcomes of your attribution model, you risk not to put enough emphasis on offline channels and channels that build general awareness. This is a trend we see across the board. Brands work too much on the bottom of the funnel and not enough on brand awareness. Hence, it's a fair question to ask if "attribution obsession" is ultimately killing your brand awareness and has a negative impact on total growth. Let me know, what you think.

Personally, I use a calculator but some folk prefer an abacus or scrap of paper and a pen. LinkedIn wants me to write more so I have.

TLDR: Don't calculate CAC if you are still to hit 1M ARR, and likely you'll have to experiment more to find the one channel that you feel the momentum. Until then, leave the calculators aside.

It's not only about reducing the acquisition cost. Ultimately, you want to manage the balance between CAC and CLTV (customer lifetime value) and esure that your CLTV is structurally higher. The best approach is to focus on conumer segments that bring the highest CLTV to reduce pressure on CAC. This requires a customer segmentation that allows you to understand who are your most valuable customers.