Cardlytics ($CDLX) Detailed Write-Up and Valuation
Describing interesting elements around the company. Valuing Cardlytics based under different scenarios and assumptions.
For all my notes on CDLX, check out my Qualitative and Quantitative “Research Notes”:
Company Overview
Cardlytics ($CDLX). $142/Share x 31.8M Shares ~ $4.5B Market Cap. Potential for $80B+ market cap over the next 5-10 years (described below).
Background
Cardlytics is an advertising platform, where advertisers/marketers can offer discounts to customers, primarily through the digital banking channels. Advertisers can target customers based on their anonymized purchase history, with information similar to what you could find on a bank statement. This gives advertisers a way to target customers that are not currently customers, but likely could be, based on their transaction history.
For instance, if someone frequently goes to a BP gas station, with a Conoco nearby, Conoco can see those transactions and incentivize the consumer to get gas at their pumps instead. The consumer sees the offer in their bank app and activates the offer by clicking it (green check top right-hand corner of offer). They use that card to complete the purchase. Once they complete the transaction, they will get a notification the offer was used (if turned on). After a period of time, a credit will be applied to their bank statement based on the offer amount.
Offers can vary by percentage (if they need to incentivize a certain customer more, the offer amount can be increased), dollar amount, and by total spend (i.e., an offer will say “get 10% on all purchases until a $10 maximum is reached”).
Picture of Offers:
Source: Personal Chase Account
Benefits for the Parties Involved
Advertisers
Advertisers or marketers are the source of the offers.
The benefit to them is being able to place ads in a brand safe environment. There is no risk of placing an ad next to or on the same page as content that hurts the advertiser’s brand. We have seen this with Facebook and YouTube. A couple years ago, many large advertisers had to pulls ads off YouTube, as the creators were posting content that was hurtful to their brand. It is difficult when advertisers are placing ads on channels that they do not control the content. That is not a risk when placing an ad within the bank channel.
Another benefit is the ability to target ads based on prior transactions. What people are currently buying is a good indication for what they are willing to buy or will be buying in the future.
Companies can target individuals who shop in their category, but not at their stores.
Advertisers can send offers to customers outside of their loyalty members or outside of those who have provided an email.
Benefits from direct feedback loop, of seeing the effectiveness of the ads. Also, can now advertise on Dosh first, see the success of the ads, and then rollout a larger and longer ad campaign on the bank channel.
Consumers
Customer, cardholder, consumer. These are the individuals targeted, who activate and use the offers (consumer incentives).
Benefits from personalized offers and will benefit more from additional ads and as targeting increases.
Enjoys using offers to save money, without having to physically give a coupon to cashier (all on card).
Saves money on transactions they were already going to buy.
Centralized location of many offers, to help decide where to eat, shop, travel, etc.
Banks
Able to earn additional revenue from monetizing data and serving the ads.
Benefits from increased use of their app or online banking platform.
Benefits from increased use of their cards, over others in a customer’s wallet. If one card has a great offer, the customer will likely use this card over others when making a purchase. Beyond the financial component, this is another reason banks would prefer Cardlytics over something like Google Pay, where the offer can apply to any card the customer chooses. (More info on Google Pay below).
Cardlytics
Benefits from earning revenue. Revenue is the portion of billings paid by advertisers after the consumer incentive or offer is funded.
I.e., Cardlytics Revenue = Billings - Consumer Incentive.
Comparison to Other Ad Platforms
Solicited vs Unsolicited
The most important comparison, that is rarely discussed, is how the advertisements (offers) on Cardlytics are welcomed and solicited. Consumers must decide to look at the offers. In other advertising channels, advertising is done where the eyes are at, and typically, if not always, the consumer is not viewing that channel for the purpose of ads.
It is true that consumers may see the offers on their banking app when they are viewing it for purposes of checking their bank statement. However, to view the larger selection of offers, a consumer must click on this option.
In all other ad platforms, advertisers have the headwind of consumers not wanting to see the ad, and either mute the channel, turn the channel, skip the ad, use Ad Block, or other alternatives to avoid it. This is not the case with Cardlytics. Consumers choose and enjoy looking at the advertisements.
Source: Personally Created
Consumer Propositions
Selection Size
Currently, there are not many offers, which is one reason many consumers do not use the offers (less offers and also less relevant offers). As the number of offers increases, the likelihood of offers being applicable to the consumer increases.
As the number of offers increases, the value to monthly active users (MAUs) will increase, as they will enjoy looking at the different offers available and can use this to decide where to shop, eat, or travel.
Price
Free for the consumer to use with their existing credit and debit cards.
The offers lower the prices you pay, so consumers are saving money.
Convenience
By having all the possible offers in one central place, you can compare what the best deals are at that time, swaying your decision on things such as where to eat. Why go to Subway when you have 25% off Jimmy Johns? I have found myself checking the offers first before deciding where to eat or which hotel to stay at for a trip.
Service / Experience
Better than coupons, since offer is linked to your card, and the discount will be applied without the cashier knowing. May be a small point, but there are some negative stigmas around using coupons, so if Cardlytics is able to avoid that, all the better.
Extremely easy to activate and use offers.
Dosh
Cardlytics’ acquisition of Dosh could have some positive long-term impacts, beyond short term improvements. See below for a visual of how CDLX and Dosh could possibly fit together.
Description of Company
Dosh also allows for card linked offers. The offers are more in line with the cash back offers you see offered by other banks or cards. Where most alternative options, such as at credit unions or major credit card companies, offer 1.5-2% cash back on all purchases and up to 4-5% on select categories, Dosh has specific company cash back offers that are anywhere from 2% to 10%, with some higher.
Where This Helps
Integration with smaller FI’s, smaller banks, neo-banks, etc.
Previously, it was difficult to imagine smaller banks being added to the Cardlytics platform, given their long integration times. With Dosh, smaller banks attracted by additional revenue potential can now be more easily added and with shorter integration times.
Testing of new ads before rolling out larger and longer campaigns on bank channel.
An additional benefit is the ability to test new ideas and offers on the smaller user base of Dosh. The insights from these tests can then be used to roll out larger ad campaigns on the bigger banks. This could be valuable when combined with the self-service platform.
It is possible that ad agencies and advertisers are using the “Cash Flash” on Dosh as a way to test out a higher offer amount that is more in line with what you would see as a one-time offer on CDLX, before rolling it out on the bank channels. Typically offers on Dosh are more in line with the smaller cash back offers that other banks and cards offer, such as around 5%, while on Cardlytics powered platforms, the offers are typically one time offers that are greater than 10%.
Increasing network effects
The ability to add smaller FIs and neo-banks will add more MAUs, making it more attractive for advertisers, which will increase ads / offers on the platform, which will increase usage and activation by MAUs, leading to increased revenue, which leads to more banks wanting to be a part of the system, and so on.
Sharing of advertisers
We have already seen this at play. Advertisers that were only on Cardlytics, have now begun advertising on Dosh. And advertisers that were only on Dosh, are advertising on Cardlytics.
Each company has done certain things well and certain things poorly. Management of Cardlytics should spend some time thinking things through with adequate testing, before simply taking features of one and adding it to the other. One feature that seems to be discussed frequently is Dosh’s non-activation model, where consumers do not need to click/activate an offer for it to apply to the related transaction. CEO Lynne Laube specifically mentioned they will study this model. If Cardlytics begins using the non-activation model, it may lead to less engagement and less awareness of offers. In addition, it may conflict with the Cost per Served Sale (CPS) pricing model, where Cardlytics gets paid for every served sale, regardless of redemption.
Source: Personally created, but used information and small graphics from Cardlytics.
Bridg
Description of Company
Bridg aggregates product level / SKU level data at scale. In comparison, Cardlytics aggregates transaction level data at scale. Bridg is a SaaS based program, which is their revenue model. Retailers pay a subscription to get access to this platform, where they can understand and run analytics on their consumers and can publish advertisements to the open internet.
What’s Unique
60-day onboarding process
Possible to get this down even shorter.
Extremely quick in relation to Cardlytics onboarding time with large banks.
Insights into unknown customer
Most retailers only know customers enrolled in loyalty program or who provided an email.
Able to identify customers without being enrolled or providing an email.
Importance of SKU
At this time, Cardlytics does not have access to product level or SKU level data. However, recently acquired Bridg will assist with that.
Bridg can integrate easily with 90% of the Point-of-Sale systems in the United States, allowing them to aggregate SKU level data for about any retailer.
Uses The Trade Desk to send offers to customers where they do not have their emails or are not a part of their loyalty program.
Easy Integration Benefits
Before the announced Bridg acquisition, it was difficult to think through how CDLX would get SKU level data and work with companies on an individual basis for integration. This could be practical with one or two large companies like a Walmart or Target, but not tons of other smaller retailers. Bridg, with quick integration that works with 90% PoS solutions, seems to be the answer.
According to Cardlytics (see appendix), they like this acquisition because:
Bridg gives Cardlytics the ability to ingest SKU level data into their existing platform and publish content at the product level into the bank channel.
With bank permission, it would also give Cardlytics the ability to do exactly the reverse: take transaction level data combined with SKU level data and use that to target on the broader internet with Bridg's capabilities.
Bridg allows Cardlytics to think about becoming a measurement business, which could compete with companies like Nielsen.
Cardlytics looked at many companies, and this was one of the only ones that was focused on going where the industry is going. Not relying on cookies or pixels. They get their data from the retailer. The data is never sold, and never leaves the platform.
Advantages of this Acquisition
Bridg can open doors with their clients to CDLX, and CDLX can open doors with their clients to Bridg. (Similar to what we have already seen between Dosh and Cardlytics).
Will take about 2 years to develop, integrate, get banks permission, etc.
Over next year, CDLX is going to help Bridg scale with what they have. For now, CDLX can target based on transaction data within bank channel or can target based on SKU data outside of bank channel. Over time, CDLX would like to combine, but the banks would like to see Bridg having more scale first. Over time, CDLX will have SKU level offers within bank channel.
Bridg has some clients that CDLX has never been able to obtain, given these clients have required the ability to promote products for advertisements, rather than the overall store.
Comment on Prices Paid for Dosh and Bridg
Investors have mentioned that Cardlytics may have overpaid for both of these companies, specifically in relation to their individual company size, and when valuing each company on a standalone basis.
An interesting way to consider whether the value Cardlytics will receive is worth the price they paid, is to make small assumptions of the additional revenue or ARPU Cardlytics could gain from these acquisitions. Even small amounts of ARPU spread across the current 163M would have a meaningful impact.
Dosh: $275 million in cash and stock
Bridg: Approximately $350 million in cash with approximately $100 million to $300 million in earnout payments.
If you assumed the additional data or features attracted new advertisers who then increased their advertising on Cardlytics, and/or if you assumed advertisers of Dosh or Bridg now began advertising on the Cardlytics platform, and these additional offers lead to the current MAUs redeeming an additional $2 over the course of 1 year (for instance, Target may now be able to advertise, and customers on average over 1 years spend $20 and earn 10% back for $2), this would be approximately $704M in revenue (assuming 163M MAUs and $2.16 of revenue per $1 of consumer incentive, explained in more detail in the intrinsic value section), $253M in gross profit (assuming same average gross profit margin of 36%), and $108M in cash flow (assuming Dosh + Bridg operating expenses equal Cardlytics at $117M, corporate tax rate of 21%, and depreciation and amortization approximately equal capital expenditures).
Taking the present value of that additional cash flow, or using a simple 20x CF multiple, gives an additional value of $2.2B, which is in excess of the total price paid for Dosh and Bridg.
Competitive Advantages
Advertisers
From an advertiser's standpoint: CDLX vs Radio/TV/Print
Better to target based on customers that are more likely to buy, such as customers who have a history of buying similar items, rather than based on demographics of the channel. In addition, CDLX allows for better ability to see if they actually bought due to your ad (possible with radio/tv/print, but more difficult or not as concrete of data to track results).
From an advertiser's standpoint: CDLX vs internal discounts sent out via email or through app.
Targeting customers outside of your store may be better than sending offers to people who are already customers. With tracking your website, using email addresses of existing shoppers, and a loyalty system, marketers are limited to their internal store data, and not external stores / competitors. They may not know to target a customer that shops next door to them every day, since they do not have the information, while CDLX does. Also, more likely to see and use that discount from a central place, like the Chase app, rather than having 10 different loyalty apps.
Some push back has been companies have sufficient capabilities with their own apps, to not need what CDLX offers. However, these companies, such as Starbucks, still advertisers on Cardlytics, to get customers who are not on their app or who do not go to Starbucks. This is proven by the fact that their Cardlytics advertisement description mentions to download and use their app.
From an advertiser's standpoint: CDLX vs online ads like Google, Facebook, YouTube.
CDLX is more brand safe (advertising in a bank setting, rather than where you do not control all the content on Facebook / YouTube).
CDLX offers are only seen when the user wants (solicited), rather than unsolicited and typically blocked (Google / YouTube)
Banks
Banks doing this themselves.
Would require building out all the technology, hire staff, and build relationships with advertisers or create a self-service platform.
Therefore, there is likely too high of fixed costs, where an individual bank’s division handling this cannot be supported with a single bank’s MAUs with less ARPU from having less data and reach for advertisers. If Cardlytics at their scale has yet to have gross profit surpass the fixed costs, a bank with less scale will have an even more difficult time. It benefits everyone involved to pool and share resources.
In addition, advertisers need enough MAUs to make it worth advertising on that platform, and therefore a single bank’s MAUs may not be enough to appeal to advertisers. This has been where CDLX has struggled in the past, and now given their larger MAU base, it is why investors cannot assume that previous ARPU levels will stay constant.
Due to doing everything in house, an individual bank will not have the resources to support small advertisers (without a self-service platform), which limits the number of offers, and becomes less attractive to the consumers.
Cardlytics
Vs New Competitor
Network Effects and Scale: Similar to the discussion on how Dosh and CDLX fit together, as more FIs and other banks join the platform, the number of MAUs increases, which increases the appeal to advertisers (more reach and more data), which increases the number of advertisers and number of offers, which increase the appeal to MAUs (more offers and more relevant offers), which increases usage and ARPU, which appeals to the banks and leads to more banks adding the platform, and so on. This is an advantage, as banks want to go where the most advertisers and revenue potential are at, and advertisers want to go where the most data and MAUs are at, making it difficult for competitors to enter this area.
CDLX already has most of the large banks in the US, so new entrants will not be able to scale fast enough to overcome fixed costs by obtaining smaller banks, given the high fixed costs required to operate this business. If Cardlytics at their scale has yet to have gross profit surpass the fixed costs, smaller competitors with less scale will have an even more difficult time.
Need to gain bank’s trust to use their data and be able to integrate with their systems. CDLX was able to gain this trust, likely from having founders that were previously bank executives.
Difficult to gain other banks to join your alternative platform. The reason is, if you were a small bank, and trying to decide to go with CDLX, or a new competitor, most would feel if Chase, Wells Fargo, Bank of America, US Banks were trusting their much larger dataset and amount of money with CDLX, you as the small bank should also be able to trust them.
It will be difficult to start from scratch and catch up to CDLX, given CDLX started many years ago.
Given security concerns, a bank channel would not likely service two different offering platforms, making CDLX the only platform on a given bank channel.
Vs Google Pay
One competitor who could gain some market share in this space is Google Pay (future for Apple Pay as well).
Through their digital wallet, they have a similar area for advertisers to place offers.
Google Pay may have an advantage, where advertisers are familiar with using Google to place ads, and Google likely can combine their other data to have additional insights for marketers for targeting purposes.
One area where they lack is in terms of being limited to purchase history that is on Google Pay. It is possible Google Pay only can collect payment information from the transactions made on Google Pay, and therefore does not have the complete purchase history of an individual, from purchases made on a physical debit or credit card. This could change. And with time, it is possible 100% of purchases will be made on a digital wallet, which will likely happen once personal IDs are made mobile, as this would remove any need to carry around a wallet. For now, many SMBs are still without the Google Pay option, which gives CDLX time to grow their marketing bases.
Both CDLX and Google Pay can exist, and not be one or the other. Ads placed on Cardlytics can be used with cards used in person, with Google Pay, Apple Pay, etc., where ads on Google Pay are limited to payments made via Google Pay. Additionally, if all advertisers started placing offers on Google Pay, an advertiser may be more seen if they are the only offer on Cardlytics.
Google Pay is not limited to Android users in the sense of restricted use. But rather, as an Apple user, with Apply Pay easily accessible and embedded on the phone, will an Apple user use Google Pay over Apple Pay, or use both options? If not, then a large portion of the market will only be on Apple Pay, which limits the ad reach of Google Pay offers. Therefore, if you project out the scenario where 100% of transactions are on a digital wallet, Cardlytics still works. A way to visualize, is where all Chase users can be serviced via the Chase App, and their offers still work on all digital wallets. While if that same offer is on Google Pay, the advertiser is limited to the population using Google Pay. Therefore, an advertiser can either just use Cardlytics to place an offer that works everywhere and on all wallets, or they can place the ad three or more separate times on each digital wallet advertising platform.
Cardlytics also has the support of the underlying banks and cards. Beyond the financial component where the banks get a cut of this ad revenue, with Cardlytics, the banks benefit from increased use of their cards, over others in a customer’s wallet. If one card has a great offer, the customer will likely use this card over others when making a purchase. This is another reason banks would prefer Cardlytics over something like Google Pay, where the offer can apply to any card the customer chooses. It is possible if you extrapolate this out, and all cards are on a digital wallet, no individual card or bank will get any transaction lift from the use of digital wallets, since the customer can go back to using the same card they always use and apply offers to that same card. But with Cardlytics, since the offers are card specific, a customer has incentive to use that specific card, and still able to use it in their digital wallet.
Areas for Growth
Advertisers
Higher Average Revenue Per User (ARPU)
More advertisers, such as smaller companies starting to place offers on the platform.
Increase of higher spend offers, like travel and luxury.
Shift from tv spending / print / radio to digital ad spending, such as on Cardlytics.
Shift from other platforms, given that offers / ads can be more targeted, given data from credit and debit card transactions.
Shift from riskier ad platforms, like YouTube, where there is less control on the content, leading to risk of damage to brand. Safe and receptive environment for ads via banks.
Shift from less targeting ability due to less data, such as from Apple and their recent restrictions. Compared to other advertising platforms, such as those that track app activity on an Apple iPhone, and with the recent changes Apple has enforced, it may make CDLX more appealing. Cardlytics does not primarily use this data for ads. This makes Cardlytics data on purchase history for targeting slightly more appealing in relation to other digital advertising platforms.
Self-service tool would allow companies / ad agencies to do ads on their own. This increases number of advertisers Cardlytics could service (no longer doing it themselves).
Consumers
Increase in MAUs:
Over many years, we will see the current older generation being replaced with a younger generation who use mobile and online banking more. With this increase, you should see a natural increase in MAUs with the existing bank partners.
Increase in ARPU:
Adding notifications would increase awareness of offers in general, and specific offers, leading to more usage and redemption.
Less friction of activating offers, possibly from not requiring activation like on Dosh. Risk is secondary effects, such as not requiring someone to activate the offer may lead to less checking of the app, and therefore less awareness of the offers out there. In addition, it may conflict with the Cost per Served Sale (CPS) pricing model, where Cardlytics gets paid for every served sale, regardless of redemption.
More awareness from current users via ads (Chase Offers has previously advertised on Facebook).
More use after targeting improves and offers become more relevant.
More touchpoints, such as email. This will lead to more use / awareness / probability of activating and using.
Banks
More MAUs from the additional MAUs from the new banks. It is still possible for American Express to be added to Cardlytics. However, it seems more likely to gain additional MAUs via Dosh with smaller banks and neo-banks.
Additional ARPU, as more MAUs lead to more advertisers becoming interested, leading to more offers, more usage, and more ARPU.
Cardlytics
International expansion with open banking. Disadvantage is its one customer at a time, rather than millions of users all at once. The reason is due to requiring each customer to allow Cardlytics to work with them, on a user-by-user basis.
Change pricing with marketers to decrease their return on ad spend (ROAS), since higher than most other channels.
Improving platform capabilities to increase ad spend and attract more advertisers.
Offers to motivate specific purchases via SKU level offers via Bridg. Bridg has some clients that CDLX has never been able to obtain, given these clients have required the ability to promote products for advertisements, rather than offers at the overall store level.
Offers to motivate ordering online and pick up, which may be quicker, easier, and lead to more revenue for certain companies. This ability would attract additional advertisers.
Offers to motivate usage during certain times, such as when the business is less busy. This has been seen on Dosh already, with Popeyes and Dunkin Donuts. This ability would attract additional advertisers.
Enhanced user interface, allowing more than a logo of the company.
New Revenue Streams
Using data to help lenders with better information, but unlikely, since requires sharing data regarding a specific individual.
Help real estate planners decide where to build and buy based on transaction locations.
Add additional revenue from entering the measurement business, like Nielsen.
Other services integrating with Cardlytics to be a platform that analyzes and advertises for you. For instance, small businesses, that do not have the resources to understand how to advertise on Cardlytics or analyze the data. This service could be created by a 3rd party using the self-service platform. Cardlytics and banks still benefit, since they get paid for the ads purchased.
Psychological Factors
Based on factors described by Charlie Munger.
For Consumers
Incentive Caused Bias: Offer for discount on purchase is incentivizing you to make use of that offer and make the purchase.
Availability Misweighing Tendency: Having an offer in front of you, that is available to you, may make you think about going to that location over others (buy coffee that day at Dunkin’s vs Starbucks), simply by seeing that offer and now thinking about that company.
Commitment Bias: By clicking to add to your card, you have a sense of committing to using it.
Deprival Super Reaction Tendency: By activating an offer that is time bound, you may feel that you need to use that offer before it expires and lose that offer.
Reason Respecting or Justification Tendency, and Liking Tendency: Users may enjoy seeing the total amount saved increase within the app, and use that has justification for buying more of something.
Operant Conditioning with a Variable Schedule of Rewards: Given that the timing of when new offers appear is random, as well as the number of new offers, users may find themselves over time checking back with the app at unusual rates, in almost an addicting manner.
For Banks
Consistency / Commitment Bias: Once a large bank is integrated with Cardlytics, it is very unlikely they will switch. The biggest reason is it takes months of work to get the system integrated. Therefore, there are high switching costs, not just financially, but time wise, for them to switch to a new platform.
Social Proof: If you were a small bank and trying to decide to go with CDLX or a new competitor, most would feel if Chase, Wells Fargo, Bank of America, US Bank were trusting their much larger dataset and amount of money with CDLX, you as the small bank should also be able to trust them.
Interesting Factors
Short-Sellers: Not necessarily a high percentage of the float is short, but there is approximately 10% of the float shorted. If Cardlytics can do well in the future, there will be some level of short sellers who will need to repurchase their shares, possibly helping increase the price of the company higher. More importantly, seeing this level of short interest gives some comfort as to why there is such a large disconnect between the current price and estimates of intrinsic value. Many investors do not see value in this company, they believe banks can do it themselves, they see it as an old card linked offers system that advertisers will no longer use, and they see no real proof in earnings yet. These factors could all be proven wrong in time.
Inflation: As prices of consumer products, food, travel, and others increase due to inflation, Cardlytics should benefit slightly. The gain on revenue from inflation in dollars should outpace inflation of wages and other fixed costs in dollars (essentially mentioning the benefit of operating leverage).
Intrinsic Value
Simple Thesis
As a more unique way of valuing Cardlytics, I started by taking the average redemption, or consumer incentives (CI), between my friends and family that are eligible, and redeemed within the last 1 year. This was an average of $24.3. Average of $75, $72, $9, $8, $3, $3, $0 = $24.3. (This is a small sample size, and therefore more intrinsic value calculations are done below). I will assume that within 5 - 10 years, all MAUs will have an average annual redemption of $24.3.
x$2.16 of Revenue per CI = $52.5 of average revenue per monthly active user (ARPU)
x163M MAU = $8.6B total revenue
x36% gross profit margin = $3.1B gross profit
-$200M in OpEx & 21% Tax = $2.3B cash flow
x20 CF multiple = $46B.
(Assumptions are listed further down below)
For reference, $52.5 of ARPU seems reasonable to obtain in the next 5-10 years, in comparison to other mature digital advertising platforms. In addition, as travel and luxury offers increase on the platform, as more offers are added, and as awareness increases (Cardlytics has waited to send more notifications to MAUs until enough offers or relevant offers are on the platform), one could expect that ARPU would increase from current levels to something more in line with the larger digital advertising market, especially with regards to the advantages of this platform in relation to others discussed above.
Conservative Value
Beyond ignoring growth in monthly active users (MAU) and ignoring more redeemed offers as more ads come onto the platform, I will assume average redemption or CI is 25% of the average $24.3 listed above, still within the next 5-10 years.
This leads to an average redemption or CI of $6/year.
This can either be viewed as assuming there is a larger portion of the MAU base that will not use offers or contribute $0 of ARPU. Or, this could be more looked at as a way to bring ARPU more in line with ARPU earned on the lower end of the digital advertising market.
Using the same assumptions and numbers above, results in a market cap of $9B.
Worst Case Scenario
Probability of bankruptcy is low given current levels of debt are minimal.
Probability of equity value becoming worthless is low, as long as CDLX maintains the rights towards advertising on 160M+ users through the bank channel. That is a large advertising base, that is worth something in of itself. It is not worth $0, but nor is it worth the current market cap of $4.5B without producing advertising revenue.
Overall, probability of $0 value is low, but not non-zero.
Current Scenario / Current Market Value
Reversing it based on the current market cap (approx. $4.5B), essentially a reverse DCF, keeping all assumptions, backs you into an average redemption of $3.82/MAU.
Assuming users on average are redeeming a 10% offer, on a $10 item, this is less than 1 offer redeemed per quarter.
Therefore, this situation currently has a possibly protected downside, with a good potential upside.
Assumptions
$2.16 of revenue per $1 of consumer incentive (CI) is based on the average of the last 3 years of numbers within the 2020 10-K. This number includes numbers under both pricing models of Cost per Served Sale (CPS) and Cost per Redemption (CPR). Given that the CI reported in the 10-K is likely only the CI that Cardlytics was required to pay under the CPS model, and therefore does not include CI paid by marketers directly under the CPR model, it may be more appropriate when basing figures off of CI, to either assume all CI is under the CPS model (and therefore matches the 10-K), or to be more conservative and assume that it is under both CPS and CPR but then take a portion of that total (to adjust it to match the 10-K) and still use the $2.16 figure. This second method of calculation is done below.
163M MAUs is based on current 2021 company data.
36% gross profit margins are from the average of the last 3 years.
$200M OpEx (operating expenses) is based on the last 3 years, with an added margin due to the assumed increase in expenses from the recently acquired companies (Dosh + Bridg). This expense will grow over time but will remain generally fixed in relation to growing revenue, and therefore provides operating leverage.
21% tax rate (could very well increase over time).
$6.5M of CapEx (capital expenditures) is based on the average of the last 3 years, which is approximately equal to the average depreciation and amortization of $5.2M over the last 3 years, so these have been cancelled out and ignored, especially in light of their size in relation to revenue.
20x CF multiple can be looked at as a modest multiple that investors may be willing to pay for a mature CF generating business with growth potential. Also, could be thought of as the present value of all future cash flows, discounted at the risk-free rate plus an equity risk premium and growth factored in. Assuming an average future 30-year treasury rate of 5%, an equity risk premium of 3% once stabilized and mature, and a growth rate of 3%, PV = CF / (i-g) = CF / (5% + 3% - 3%) = CF / (5%) = 20x CF.
More Realistic Value, Changing Assumptions
If you keep all the assumptions the same but believe in the next 5-10 years MAUs will grow from more banks and financial institutions using Cardlytics or Dosh, and from the gradual increase in users of digital banking, 200M MAU seems reasonable.
Also, if investors would pay a multiple similar to other companies whose primary source of revenue is from digital ads, a 20x cash flow multiple is fairly low, especially given the length of the future runway. Therefore, more realistically one could assume 30x FCF would be paid by investors.
The average redemption, or consumer incentives (CI) = $24.3.
x$2.16 of Revenue per CI = $52.5
x200M MAU = $10.5B
x36% gross profit margin = $3.8B
-$200M in OpEx & 21% Tax = $2.8B
x30 CF multiple = $85B.
More Realistic Value, Changing Assumptions, CPS vs CPR Pricing Model
Cardlytics has two primary pricing models, Cost per Served Sale (CPS), and Cost per Redemption (CPR). Under CPS, Cardlytics is paid regardless if the consumer redeems the offer when completing their sale, but under CPR, Cardlytics is paid a separate fee, and only when the offer is redeemed. Therefore, it may not be appropriate to assume the full $2.16 of revenue per $1 of consumer incentive, since this assumes all consumer incentives are from what Cardlytics pays under CPS. Therefore, it may be more appropriate to assume that the consumer incentives we are using is for the total amount redeemed by MAUs under both CPS and CPR, and to match Cardlytics 10-K, we need to make an assumption of the portion of consumer incentives that is paid by Cardlytics under CPS. If we assume that is 70%, since CPS is Cardlytics primary revenue model, and keep the assumptions the same:
The average redemption, or consumer incentives (CI) = $24.3 * 70% = $17
x$2.16 of Revenue per CI = $36.7
x200M MAU = $7.35B
x36% gross profit margin = $2.65B
-$200M in OpEx & 21% Tax = $1.93B
x30 CF multiple = $58B.
Value Based on Percentage of Total US Digital Ad Spend
If total US digital ad spend was $200B within the next 10 years (excluding political ads), and Cardlytics earned 2.5% of that as billings, that equals $5B worth of billings, and approximately $3.35B in ad revenue.
x36% gross profit margin = $1.206B
-$200M in OpEx & 21% Tax = $795M
x30 CF multiple = $24B.
This ignores international revenue.
Average Intrinsic Value
If we take the average of these scenarios, or said differently, we found the expected intrinsic value and assumed equal likelihood of each occurring, and we ignored the $0 scenario (addressed immediately below and in the Kelly Formula section), we would have an expected intrinsic value of $44B (average of $46B, $9B, $85B, $58B, $24B, or 20% probability of each scenario occurring).
However, even if you assumed a 75% likelihood of the company being worth $0, and a 25% chance for the other scenarios (5% each), the expected value would be $11B, which is still above today’s market price.
Kelly Formula
The Kelly formula is used to determine how much to bet of a bankroll. This formula has been used successfully in games like Blackjack. The higher the probability of success, and the higher the payoff, the more that should be bet. But even with a significantly large payoff, if the probability of success is small, betting anything when there is a non-positive Kelly ratio may not be rational, such as with lottery tickets.
It should be noted, these percentages are highly subjective, and are only two scenarios, that would only occur once. This is different from a something such as 10,000 coin flips, where with the law of large numbers, the probability of heads and tails will likely equal the 50% you would expect with a fair coin. However, with 10 flips, you may see percentages of 25% heads and 75% tails. Therefore, since these percentages are both subjective and for few scenarios, the Kelly formula should not dictate the size of your position but should rather give you some guidance if the percentage of success vs failure and in relation to the gain in proportion to the loss makes it a viable investment.
Bet Size = Probability of Success / Percentage Loss – Probability of Failure / Percentage of Gain
Scenario 1: 25% chance of going to zero, 75% chance of non-zero expected payoff.
Probability of Success = 75%
Probability of Failure = 25%
Percentage of Gain = 44B/ 4.5B- 1 = 878%
Percentage Loss = 0M / 4.5B – 1 = -100%
CDLX Bet Size = 75% / 100% – 25% / 878% =72.2%
Scenario 2: 75% chance of going to zero, 25% chance of non-zero expected payoff.
Probability of Success = 25%
Probability of Failure = 75%
Percentage of Gain = 44B/ 4.5B - 1 = 878%
Percentage Loss = 0M / 4.5B – 1 = -100%
CDLX Bet Size = 25% / 100% – 75% / 878% =16.5%
Therefore, even if you consider there is a 75% chance of the company going to zero, with the other 25% likelihood of the company succeeding and is valued at the average of the intrinsic values, this investment at the current market price may still be a worthwhile investment, given the potential future payoff.
Biggest Risk
If new advertisers do not join the platform and add additional offers to the mix, you will not have enough applicable offers to push awareness and use by MAUs. Users have no incentive to use offers that do not appeal to them or are not applicable to them. Without more marketers advertising on the platform, revenue will stay flat or decline, decreasing the value of the company.
Catalysts
American Express (AmEx) joining the Cardlytics platform (low probability for now) is one catalyst towards closing the gap between current price and intrinsic value. AmEx would join out of the need to be a part of larger scale, to get access to more marketers that require the additional advertising base to make it worth it to advertise. AmEx would want this, as it adds more revenue than they would be earning on their own, even if their retained portion of revenue is lower.
Another catalyst is the self-service platform put in the hands of more advertisers, leading to more ads, more MAU usage, more revenue, more CF, and then higher value assigned by the market.
Conclusion
Due to competitive advantages and current scale, Cardlytics is well positioned in the digital advertising area. The targeting ability based on transaction and purchase history becomes more appealing as other restrictions apply on other advertising platforms. With psychological factors acting as a tailwind, and given the potential upside from the current price in relation to multiple ranges of intrinsic value, there seems to be good upside, with possible limited downside, as long as more advertisers use Cardlytics.
Follow-Up
If you have any questions or push back on any of the above, please contact me. I would enjoy discussing more and getting to the correct answer.
-Austin Swanson (Swany407)
Twitter: @Swany407
Website: Swany407.com
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Appendix / Sources
Cardlytics Website: https://www.cardlytics.com/
Dosh Website: https://www.dosh.com/
Bridg Website: https://bridg.com/
The Trade Desk Website: https://www.thetradedesk.com/us
2020 10-K: https://www.sec.gov/ix?doc=/Archives/edgar/data/1666071/000166607121000029/cdlx-20201231.htm#i3ec207e654ed4eab98c30b3eaf5c446c_67
Cardlytics Latest Investor’s Presentation: https://ir.cardlytics.com/static-files/ad3f1ebb-22de-44ce-8776-c17ca9194928
Bridg Notes: Most of the following information is from Cardlytics’ call following the Bridg announcement. Most comments were from Lynne Laube.
Cliff Sosin of CAS Investment Partners has provided much clarity and information via Yet Another Value Channel: a.
Psychological factors from Poor Charlie’s Almanack: https://amzn.to/3x7KUNA
Numbers based on 10-K:
