Creating Demand (with Merchant-Facing Apps)

This is Part 2 of the Consumer Demand Series.Introduction
‍Part 1: Merchant Front Office Apps - Setting the Foundation
‍Part 2: Creating Demand with Merchant Facing Apps
‍Part 3: Consumer Apps
Part 4: The Big Leap to Two-Sided Marketplace

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Great companies have ambition in excess. For vertical SaaS vendors (VSVs), there probably isn’t a more ambitious and audacious move than extending towards consumers. The road is narrow and the way windy, but companies that walk this path can build a highly defensible, profitable, and enviable business.

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In Part 1, I discussed front office applications that help a merchant engage and transact with customers. However, those applications stop short of actually generating net new consumer demand. 

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This is a critical departure. If effective, it allows a merchant to proactively grow their business and a VSV to dramatically increase their value in the merchant’s eyes. I would argue that companies pursuing incremental demand need to take an inside-out approach:

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1. Start with value propositions that are closely tied to the front-office apps from Part 1 to help increase conversion.
2. Then, proceed to applications that explicitly provide demand.
3. If possible, leverage multi-merchant network effects to create co-ops (data, identity), ad networks (custom audiences, trade marketing), common-payer schemes (aggregate supply pool), and consumer networks (loyalty, demand pools).

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Creating truly net-new incremental demand is the holy grail for VSVs. The VSV that can say, “When you buy our software, you will grow faster than all the other stores on your block,” is the VSV that wins. However, there are many steps to take before demand generation becomes your primary offering. 

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Step 1: Increasing Conversion & Cart Sizes

One of the easiest ways for a VSV to create incremental demand is by leveraging the front-office apps it has already built to increase conversion rates or cart sizes. (Recall the chart outlining all of your front-office app options from Part 1). These approaches create more revenue for merchants, and VSVs can often charge a take rate. There are a few ways to do this:

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Personalization, Recommendations, and Bundling

Through leveraging CRM data, a VSV can personalize a shopping experience, increasing conversion by providing recommendations during purchase. For example, Mr Yum, out of Australia, started with a simple tool that allowed restaurants to build visual menus accessible via QR code. From there it has expanded into building a CRM with a personalization and recommendation engine. By tracking repeat customer purchases, the software can customize the menu to individual customer preferences. The more customers that use the product, the more targeting data the algorithm will have, and the better the recommendation. If a profile shows that a customer loves dumplings, the menu will surface a promotional dumpling appetizer, driving additional ticket items that would have otherwise been ignored.

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Price/ Revenue/ Capacity Management

Many VSVs have real time read/write access to a merchant’s inventory, and the ability to execute dynamic pricing changes and promotion campaigns. As a result, the VSV can dynamically lower prices to try to sell underutilized or unsold inventory, or increase prices when inventory is scarce. This is most powerful in situations where the inventory is perishable (e.g., seats at a venue) or has low marginal cost (e.g., digital goods). For an example of what it looks like for digital goods, Substack can automatically run dynamic promotions and pricing for their writer merchants. We’ve found that the more creative a VSV can be in managing prices—through bundling, promotions, financing, or price discrimination—the more margin they will likely capture. 

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Another great example is Isaac in edtech. It helps its private school merchants sell unsold inventory (seats in a classroom) by lowering the effective price. However, rather than lowering the explicit price, Isaac reduces the barrier to purchase by offering families tuition financing. Isaac buys seats from the school at a wholesale discount and charges tuition at retail price, creating a spread to offset any defaults. 

Access to Credit 

Isaac is also a great example of a broader opportunity to offer credit to reduce perceived price (and increase conversion). The most prominent example of this is Buy Now, Pay Later (BNPL) with companies such as Square/Afterpay and Klarna. These vendors offer consumers the ability to easily purchase items on credit, which has been shown to increase conversion and cart size and overall consumer demand. The product has enough utility that many consumers now start their shopping on a BNPL app. Afterpay has reported 30% of searches start with BNPL and that they send millions of leads to their merchants.

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Fraud and Risk 

Fraud at the point of sale remains a problem for all merchants. Bad actors will issue fake chargebacks or use entirely fraudulent accounts to purchase a merchant’s goods, leaving SMBs holding the bill. By properly calibrating risk—letting more of the good customers in and keeping the bad customers out—a VSV could increase conversion and likely earn a take rate (you can look at horizontal players Sift and Signifyd as an example). While I haven’t seen VSVs provide this service directly, I think either embedded or industry-specific services will emerge soon.

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Step 2: Acquiring Customers

Once a VSV has built out front-office incremental demands apps, the next step is to move towards explicit demand generation. Many SMB merchants lack the time and expertise to manage digital demand generation, and a VSV will have the advantage of both scale and scope via their huge varieties of data sets.

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Channel Manager → Meta Search

A VSV that has channel management can leverage its position in the booking flow to deliver and monetize demand. Channel managers integrate real time inventory in the property management systems (PMS), and sell that inventory on demand channels like marketplaces. A channel manager can create its own demand channel at the same take rates as the marketplaces—if the channel manager sources demand from lower-cost channels, it earns the spread.

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As an example, SiteMinder’s core product is a SaaS platform that helps its hotel merchants integrate into Online Travel Agencies (OTAs) such as Expedia and Booking.com. Using the same infrastructure, SiteMinder also offers “SiteMinder Demand,” where it receives a booking fee on any non-OTA demand it can source for its hotel merchants. Thus, SiteMinder can pursue consumer portals such as Google, Facebook and Pinterest, meta travel sites such as Tripadvisor, and even bid directly on media to source demand. And because SiteMinder Demand looks like another OTA to its merchant base, SiteMinder can garner traditional OTA economics. (For more, see our SiteMinder case study).

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Media Buying and Lead Generation

When a VSV owns the booking path and has access to inventory, it may be able to acquire customers more cost-efficiently than its SMB customers. This product is typically sold on a managed-services basis, where a VSV charges a percentage of media spend. 

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Lead generation is a variant of this model where the VSV charges on a per-customer basis. The VSV is taking some risk with the difference between the cost of acquisition and the price of the lead, but they are able to potentially a) merchandise multiple merchants, which should benefit conversion or b) sell the same consumer lead to multiple merchants, which can increase monetization. From 2005-2010, lead gen models became suspect because of a temptation to sell the leads too many times, which translated to lower quality and lack of follow-up from the merchant—resulting in a bad customer experience. Ideally, the VSV can improve the lead model with better scoring and targeting, and integrate directly into the merchant workflows to provide more effective follow-ups.

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While the theory makes sense, I have not seen real-life proof of this approach. Buildium acquired All Property Management, and Sparefoot merged with Sitelink to integrate software with lead generation, but neither have had publicly positive results.

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Step 3: Getting Better with Merchant Density

The reality is that none of the capabilities I have discussed are unique on their own. However, a VSV can play an entirely different game by leveraging their most unique asset—merchant density. This community of merchants allows the VSV to do things horizontal players can’t hope to match. 

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A data co-op is perhaps the easiest example to grok. While VSVs may not have a consumer brand or a direct consumer relationship, they do have depth and scale in transactional, SKU, and consumer data. If applied thoughtfully and in a privacy-safe way, VSVs can co-op this data to facilitate consumer demand. 

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Identity

Shopify Pay is perhaps the most impressive modern data co-op. Shopify Pay dramatically speeds up the check-out process with its verified identity network. The more merchants that join the network, the more consumer identities are added in, and the more likely it is that an expedited checkout process can be offered. Login and payments information are a critical conversion point, particularly in a mobile experience, so an identity offering is a win/win for merchants and consumers. At scale, an identity co-op means that the “you should build on Shopify” pitch includes delivering a unique customer cohort with significantly higher conversion rates.

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Custom Audiences/ Lookalikes

Facebook Custom Audiences is the granddaddy of co-op databases for ad targeting. The concept actually originated from services where merchants explicitly donated their data. Abacus was the most prominent: it was a targeting co-op where catalog retailers would share their customer credit card transactional data. Abacus would then sell back a high-intent prospect list that had been scored by a collective view of all the catalog retailers’ data. 

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Historical side note: Abacus later was acquired by online ad serving company DoubleClick, which was later acquired by Google in 2007, sparking some of the first major scrutiny of consumer privacy and market power in Internet platforms. Then the DoubleClick acquisition was key to scaling YouTube’s ad infrastructure. Oh, what tangled webs our ad tech acquisitions create!

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Shopify's early experimentations with its data network of opt-in conversion data appears to be heading down a similar path to Facebook Custom Audiences. Merchants can offer their customer data into the shared data warehouse, Shopify will create a custom list of customers who would be interested in your specific product, and you can then utilize that list with other advertising platforms (e.g. Facebook). 

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For now, this is mostly used as an efficient way to create leads lists for retailers. To account for the impact of Apple’s “privacy” rules, Shopify released Shopify Audiences, which allows merchants to port lookalike audiences directly into the ad platform of their choice. This matters because it means the merchant never receives direct access to the other merchant’s customers data, but it can still be used to improve ad performance. Beyond that, the company has its own consumer app Shop that aggregates merchants’ inventory for consumers to browse. There is an AI chatbot that can recommend goods, and it seems primed to one day have ads of its own. 

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For an example of what ads look like at scale, Instacart is the leader. The company is making 2.6% of their GMV, or 1/3 of their revenues, (roughly $1 billion annually) selling ads. It's something that ecommerce companies like Shopify could and perhaps should be doing. On the other end of the spectrum, once you become a full marketplace, it can obviously work—just look at Uber expecting roughly $650 million in annual ad run rate in 2023 and Amazon making more money than God with their ad business. 

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For the VSV specialists (like our portfolio company Dutchie, essentially a Shopify for cannabis), they would be able to build out rich targeting data because of product specialization. It's even something that point-of-sale companies like Toast can consider. Other VSVs who offer Shopify-like functionality will cut their merchants in on the ad revenue, which transforms ads from a cost center to a profit center for merchants. It changes the monetization model and makes switching costs challenging. We don't know yet the best version of ads for a VSV, but there are many who are working on it. 

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In-Store Marketing (Trade Marketing)

Few people know that in-store marketing (think grocery store end caps) rivals digital marketing spend in some categories, despite ad units remaining painfully analog. Measurement is crude, with aggregated point-of-sale data to measure volume changes on a weekly batch basis. Sometimes data is only available on a monthly basis!

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I’ve seen two approaches to try to work around this constraint:

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1. Retailer specialists: Some networks form co-ops by specializing in a specific type of store. One example of this is SKUPOS, which focuses on independent convenience stores. Their significant market share means they are well positioned to provide channel volume data like IRR on a real-time basis. Their product integrates directly with most point-of-sale solutions, giving them the ability to directly measure marketing effectiveness. They also coordinate campaigns, sending marketing materials to the right retailers at the right time on behalf of brands like Coca-Cola.
   
   
2. Goods specialists: Other emerging companies will specialize in building out good-specific networks. One example is Thirstie, for liquor. On their platform, liquor brands can create a private label gift card. Since Thirstie owns the point-of-sale endpoint, it allows a CPG to ensure that its gift card is only used on its products. For example, Grey Goose can know that their gift card will be used on their vodka and not any other alcohol brand. This enables the CPG to pursue loyalty rewards and viral gifting opportunities to capture consumer data. Typically, retailers are incredibly hesitant to allow a brand to get in between them and the consumer. A service like Thirstie allows CPG companies to offer gift cards while being comforted by the knowledge that they aren’t driving the sales of a rival.

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Loyalty

Multi-location loyalty programs grow in value as more merchants sign up. These networks can be organized by parent brand (often seen with hotels or restaurants), by category (such as a diner card), or by geography (such as a Boston card).

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Supply Pool

A supercharged version of loyalty is bundled supply. A VSV can aggregate many local merchants with a common consumer experience, preset pricing, and even a common brand. Historical examples would be a hotel brand or a health insurance network. VSVs can empower this through software to give merchants the opportunity to be part of a collective supply pool while remaining independent. 

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Some examples of VSVs providing software-powered bundled supply could be:

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• A network of childcare providers (highly fragmented) for a national employer
• A direct repair program of auto body repair shops for national auto insurers
• Rental networks. Uber and Airbnb could be viewed as software-powered marketplaces that bundle fragmented supply

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Demand Pool/ Affiliate Networks

A VSV can sometimes aggregate its merchants’ consumers to create a demand pool that the VSV can access. For example, in ZipRecruiter’s initial business model, they used their distribution software to post on job boards. When any candidate responded to any job postings, ZipRecruiter would add the respondents to an in-market candidate database. This database represented a high-intent audience of in-market job seekers that ZipRecruiter could charge employers to engage with. 

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Central to this approach is the correct economics being in place. A VSV could be central in operationalizing these economics, akin to an affiliate network, credit system, or even a derivative VSV currency of some sort. Essentially, the merchant showing the ad and acting like a publisher gets a cut of the fee that the VSV generates to show the ad.

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The demand pool concept faces obvious conflicts. It only works when the merchant base is highly fragmented. Additionally, there have to be protections against competitive harvesting, the rules need to be explicit, and there has to already be a high degree of trust. 

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I could see the demand pool approach work amongst complementary or substitute merchants. In markets where consumers lack loyalty and value variety (e.g., restaurants), there can be mutual benefit to merchants trading or sharing in-market consumers. For example, it may make sense for a hotel to promote local restaurants or tour and activity operators.

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Conclusion

What makes Vertical SaaS such a special category is the incentive alignment. More than any other type of software provider, a VSV wins when its merchant wins. A great VSV is a partner and equal that provides win-win services—Parts 1 and 2 of this series have shown this. By providing front-office app integrations that can then connect to new demand, the VSV offers a full suite of growth services. Part 3 will discuss how you can go from the front office to a true consumer wedge.

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‍Consumer Demand Series
Introduction
‍Part 1: Merchant Front Office Apps - Setting the Foundation
‍Part 2: Creating Demand with Merchant Facing Apps
‍Part 3: Consumer Apps
Part 4: The Big Leap to Two-Sided Marketplace

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CASE STUDIES RELATING TO THIS CHAPTER:

SiteMinder: Extending into Consumer Demand

AppFolio: A Case Study on Consumer Extension Options