Time for change
Interesting times for Waze, and one can only hope it is for the better. Ten years passed since Google acquired the company for a jaw-dropping $1.1Bn, and the subsidiary, it seems, is yet to find a viable business model.
While its revenue is said to rely on advertising, FourWeekMBA states Waze revenue stems from $0.002 CPI (with a minimum fee depending on business size), in addition to referral fees, as well as from car-pool fees.
Is this a viable, profitable, business model? What if the mother company cuts funding and lets the subsidiary fend for itself?
More to the point: Can Waze revise its product offering to generate substantial revenue from diverse sources, including, perish the thought, from its users?
Pain and Product
One thing is certain. Users love the product. It has become a staple on drivers' phones in many markets, and with 74% loyalty, it seems to remain on the dashboard long enough.
The value proposition to drivers is epitomized by Waze's slogan: "Outsmarting traffic together". Importantly, it is the value offered to consumers - drivers: In a worsening traffic conditions, as roads get clogged by new vehicles by the day, the promise to reach your destination earlier has caught the mind and hearts of drivers - pushing app downloads to 9.2M in 2022, second only to the pre-installed google maps.
Wait, what? Am I the only one missing Waze's value proposition for its paying customers?
Publishers' Offering, Advertisers' Value
Some publishers offer advertisers a combination of traffic and format. Monthly active users translate to impressions, which - according to conversion rates - further translates to leads.
More sophisticated publishers are able to improve conversion by either better segmentation or higher intent. Facebook excels in micro segmentation, while Google specializes in bringing high-intent users.
Both approaches yield increased conversion rates ending in better outcomes for advertisers, in turn willing to pay higher impression costs (CPI, CMP) or result based monetization (PPC, CPA).
Waze's Ad Offering
As a mostly free to use service, Waze counts on advertising revenue. Local businesses - bank branches, gas stations, and similar businesses - are lured to place a geo location pin on the maps displayed to drivers.
The premise is that enough of those thousands of commuting drivers eventually convert to paying customers - not unlike roadsigns.
If I am to judge this advertising offering, I deem it suboptimal:
Segmentation is hardly employed, as all drivers seem to be treated equally
Targeting is geo location-based, but oblivious to routes, catchment areas, and destinations
Attribution is nowhere to be found, precluding high yield result based monetization.
Let's now discuss Waze's user segmentation.
Segmenting Waze Users
All users are not created equal: While an important segment consists of daily commuters, riding to and from work, another consists of people driving for errands, another of long distance or tourist travelers. Yet another segment consists of professional taxi drivers.
The issue at hand: How valuable is each segment to Waze, in terms of advertising revenue.
The answer leans on two factors - for each segment:
The number of driver touch points over time
The purchasing intent of the average wazer
We can speculate that errand-runners may be few, but their purchasing intent is high: That is what they are on the road.
We can also guess that the number of commuters is high (as attested by rush hour traffic), but their purchasing intent relatively low: They are heading workplaces.
Targeting
In this series, let's focus on errand-runners, also known as shoppers: They took the car to get to the nearest shopping center, or in route for a specialized store someplace.
They are on the hunt, they are bound to spend, and the question is: Can Waze meaningfully externalize their flow through the system to businesses in their destination?
Let's analyze what can be known about such users:
For each destination, a catchment area can be drawn in three dimensions: Two directional and one temporal:
Where from do shoppers come from?
Does shopper origin imply on their socio economic background?
How long do they stay?
How often do they come?
Anyone familiar with catchment analysis and audience segmentation will find these questions familiar: We are trying to gauge the economic power of prospective shoppers coming down the funnel we have just defined on Waze platform.
Attribution
Admittedly, this is the hardest part.
Does advertising work at all? How much so?
How much should businesses allocate to each marketing channel?
Can we close feedback loops to assess efficiency?
While the digital publishing industry has brought cookies, remarketing, and retargeting, on the targeting front, it also brought affiliate marketing, with coupons, referrals, and deep linking to improve conversion, compensate channel partners.
The features / product ideas I suggest for Waze in my next post build on the analysis in this and previous post.
Above, I touched on identified gaps in Waze's monetization strategy, and suggested on errand-runners, driving to shopping locations, as a target for new features, pointing their high purchasing intent, and the ability to segment them by catchment area.
Identifying customer segments
Interestingly, once we segment users by geographic cells, we can now segment also our paying customers: Should the management of the Mall of America advertise to wazers flowing in Washington, DC?
They definitely would like to target shoppers from Hennepin County, with median household income above $80,000, the highest in the area.
Advertising Opportunities
For this discussion, I define advertising opportunities as meaningful consumer behavior, demonstrating increased spending likelihood.
We can identify advertising opportunities based on such data as:
Departure area
Destination
Time of day
Day of week
Frequency
In-app Ads In Waze
Suggesting ad monetization is underwhelming, Waze is sunsetting its internal ad serving in two weeks time, to replace it by Google Ads technology, whatever that means.
Till then, it offers several ad formats:
Branded Pins: Like a store sign, they inform customers that a business is on or near their route.
Search: Pops your business when customers browse within category on Waze.
Takeover: A digital billboard pops when vehicles are at a complete stop to prompt awareness and action (change destination).
Arrows: These help indicate your business is nearby (outside of the map shown).
Ad Efficiency
At best and most actionable, these ad (except the search ad) cater to impulse buyers, who might alter their route or schedule. How many drivers will eventually do that, is the question.
In a case study, Waze claims "40% YOY increase in customer visits to quick service and casual dining restaurants"
Incidentally, it is a 2023 report. I suggest post-covid patterns are also in play. In an AdWeek report from 2016, a twofold ROAS increase is mentioned, comparing to display ads. The CPM display ads commanded at the time were $2.80 CPM for google display ads, comparing to $2.00 CPI for google ads.
Crucially, the question is whether these ads are scalable in terms of average exposure (impression), and whether they convert enough drivers to actual shoppers.
I brought the four main ad formats Waze offers advertisers, and - with the exception of search - pointed at the impulsive nature of the CTA.
Another aspect I would like to dwell on is the lack of attribution mechanism, and the impact it has on the potential monetization. One wonders whether the move to Google-Ads technology was indeed influenced by that deficiency.
Attribution and Intent
As mentioned above, the search ad format is much more intent-based. We expect fewer people would use it, and we might question what sorting order would bring value to both users and advertisers:
Obviously, showing only promoted business can result in empty lists and abandonment of this feature
Do you show promoted results even when they are much farther than un-promoted businesses nearby?
How close results can be thematically? Showing clothing next to footwear makes sense, what about showing cafés in the same shopping center?
At any rate, users' intent is much higher when they actively search, and yes, it can be in the starting point of the journey.
How can Waze attribute ad-exposure to actual purchases? Is there additional value hidden, and an opportunity for charging higher fees on escalating intent? After all, this is what #google does best with its search ads. You do not simply go about your life, stumbling on ads that would, as a remote option, activate a purchase - you are actively searching!
Some of these opportunities are already implemented:
CPI (Cost Per Impression): Is it the only monetization strategy? So it seems...
CPC (Cost Per Click): Branded Pins could enable this monetization strategy, as clicks can be counted.
CPA (Cost Per Action): This monetization strategy could be implemented when users follow the CTA offered by branded pins - and navigate there. To a lesser amount, arrow ads' CTA is: reposition map, and to a lesser amount - change route.
CPC and CPA are shown to command hefty commissions. For reference, see herewhere you'll find eye popping, mouth watering commissions, ranging from dozens of cents per click, to hundred of dollars (!) per action, in select industries.
Yet, there is an even better opportunity, in my view.
CPS - The Holy Grail
CPS (Cost Per Sale) is a result based monetization strategy, where an ad is shown to lead directly to a converted lead, charging a hefty commission.
How high the commission is?
Depends on the industry and exact model, commissions vary, but are not trivial, cited from 7% to 50% in the apparel industry, for example.
Interestingly, Search ads also command higher CTR (Click Through Rate): The average CTR for Search Ads is 3.17%, while Google Display Ads have an average CTR of 0.46% across industries (Source: Store Growers).
Waze's revenue would be the product of:
impressions x CTR x CPS.
Local ads would scale only that much, due to limited number of inventory (users) in each locality.
My premise is that increased revenue on limited inventory, building on materialized purchases and higher intent audience, could produce significant higher yields.
Wearing your patience thin, I laid out a framework of constraints and opportunities Waze is facing in its quest to monetize itinerary based advertising.
It is now time to craft a product idea attempting to implement lessons learned.
Offering
To recap, we want to create an ad format (plus supporting infrastructures) maximizing revenue from errand-running drivers, going to town on a shopping mission.
We want to:
Identify or induce high intent
Display a compelling CTA
Provide shoppers with a customer journey ending in a materialized purchase
Command CPA fee, through attribution of a lead entering the advertiser's store or taking an identifying action
Collect CPS fee, for materialized purchases emanating from an in-app ad
Back-End Flow
One technological feat Waze does is transforming an itinerary - that ephemeral being just created by the driver and stretching from their current location to their destination - into an ad-slot, where ads can be placed. Presumably, the system simultaneously identifies advertisers' location on the itinerary, showing Brand-pins and arrows (discussed earlier in this thread).
Brilliant implementation. Sadly, as I demonstrated earlier, it serves ads to low drivers whose motivations are unclear, hence of lower intent, and on average, of low value.
Essential to the itinerary is the destination, which will typically have a concentration of businesses. We could not realistically display several ad-pins on the map, as users would not be able to focus on any one ad, and follow through the customer journey we want them to.
But could we let these Businesses compete on this as-slot combined of destination and time-stamp? Yes we could.
Further, could we even narrow the selection to the combination of a search; destination and time-stamp? Oh yes! And how much higher would be the purchase intent of those drivers?... Let businesses in the category of the search compete for the ad-slot.
Last, provide attribution mechanism, to benefit from users connecting with businesses; and an affiliation mechanism, to collect from actualized transactions.
Back-End Infrastructures
To support the flow above, the back-end would need the following infrastructures:
Geo Location DB (This is what Waze does best, right?)
Business DB (registered in the dedicated Advertising Exchange)
Logic layer (matching opportunities to advertisers)
Ad-Exchange (allowing advertisers bid programmatically on ad-slots)
Attribution layer (firing events when users connect with businesses over a set time)
Affiliation layer (coupon generation and redemption)
Front-End Flow
Consider the customer-facing side of this ad delivery.
The first step relies on the in-app Search scenario, using google location targeting. When a user searches for a product, service, or business using the search dialogue, they are shown promoted and organic results.
While closer results are shown first, promoted results are accentuated.
Once a user picks a result, an itinerary is drawn, and the screen switches to navigation screen. However, picking a promoted result also creates a new coupon object with a CTA.
Post-itinerary coupon: This is a unique ID item, generated so that it captures the vendor, the location, the promotion detail, and a QR code. Once the coupon is created, it is pushed to the user via in-App notification and additional communication channel (email).
Summary
This feature can be further developed, but I'll stop here. I hope I was able to demonstrate a train of thoughts leading from strategic analysis to a new revenue generating feature, with the potential to increase conversion rate. The future challenge for Waze, developing this hybrid physical and digital workflow, does not stop in the infrastructures and feature development, but in building the acquisition funnels for local businesses - at global scale.
Thanks for reading!...
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