At the same time, TaskRabbit also suffered from first mover disadvantage as it slogged through painful lessons that later competitors were able to avoid and learn from.



In the next section, we’ll look at the 6 growth dynamics governing gig marketplaces that TaskRabbit underleveraged, or missed altogether.

1. Fixed pricing improves conversion by increasing purchase frequency & volume

TaskRabbit started with an auction/bid style model where each worker would submit a bid for each job and clients would select a single bid based on a balance of price and reputation.



Auction/bid models have the advantage that they can handle a much wider range of job types and allow for workers of different experience and quality levels to bid different amounts.



But, the downside is that creating a gig becomes a multi-step process where buyers must first wait for bids to trickle in and then finally decide between a number of choices. On the worker’s side, the bid model means most bids are rejected, leading to wasted time and low utilization rates.



SideCar, out of caution around Independant Contractor classification, also went with an auction/bid model vs the fixed price models of Lyft and Uber.



Even though this put them on the right side of the law, the fixed price model vastly improved user experience, and eventually muscled them out of the ride sharing market.



Companies in the gig economy space have increasingly adopted fixed price models, even as they’ve had to grapple with the worker classification lawsuits that result.



In TaskRabbit’s case, despite internal testing showing that fixed price resulted in much higher completion rates, the entrenched expectations of their worker community resulted in major backlash for the company when they finally moved to a fixed price model in 2014.

2. Quick transactions win in the world of on-demand labor

Verticals where the gig economy has found the most traction are those where the users desire the most immediacy between desire and completion. Applications like house cleaning and car washing have struggled because lag times can be days.



In contrast, by far the most successful vertical of ridesharing is one where differences in user experience can be measured in single digit minutes.



TaskRabbit’s generalized marketplace and an auction/bid system skewed it towards longer cycle tasks that had downstream effects on ratings and reviews and repeat transactions. At the same time, this model and targeting cut it off from tasks that were immediacy-oriented tasks that were making up a bigger and bigger percentage of the gig economy.

3. Vertical-specific platforms enable scale-based efficiencies & improved user experience

Later-stage gig economy companies focused on specific verticals -- ride sharing, restaurant delivery, online tasks -- and were able to develop apps dedicated to that experience. This enabled them to invest in a category-specific customer experience.



For example, Instacart catalogued the inventory of every store and could adjust to price changes in real time. Postmates allowed dynamic tracking and ETA for your restaurant delivery. Rideshare companies invested heavily in mapping solutions and surge pricing algorithms.



But TaskRabbit was a generalized platform, and couldn’t afford to invest in such customizations. The company gradually lost ground on verticals that became dominated by more specialized companies with better user interfaces dedicated to those experiences.



For example, in the early days of TaskRabbit, one of the most popular tasks was rides to the airport. It was this insight that prompted then Zimride co-founders to start what would eventually become Lyft, forever taking away such tasks from TaskRabbit.

4. Margins are pressured from both sides

By and large, gig economy workers have no loyalty and will naturally flow to where the earnings are. This means gig economy companies must manage margins carefully, by controlling both rates and utilization so that they can attract adequate workers while also remaining a compelling proposition for customers.



Unlike its later competitors, TaskRabbit never managed to accumulate a large VC warchest that would allow it to weather price wars. That meant that when the economy improved and competitors started growing, it found itself squeezed from both sides as customers left for more specialized apps and workers left for the prospect of better pay.



Margin pressures eventually forced TaskRabbit into layoffs in 2013 before their retrenchment into a fixed price model in 2014 finally brought utilization high enough that their margins could recover.

5. Reputation systems work best on transactions where success is binary

Rideshare and restaurant delivery are task categories where the success completion of a transaction can be evaluated separately from its subjective attributes. For example, when you wrap up an Uber ride, your star rating primarily factors in whether you reached your destination in a timely manner or not. There is a qualitative range for rating the ride (or the rider), but it's narrow.



Binary success allows for simple reputation systems with clear cut boundaries, leading to more consistent service quality for demand-side users.



By contrast, one of the reasons house cleaning is a difficult market for gig economy companies is because subjective evaluation of quality is inherent in answering, “Did the house get cleaned or not?” (How clean? What does “clean” mean to you versus to someone else? etc). This leads to more variable service quality and customer experience, which feeds that vertical's other biggest challenge — the best house cleaners getting poached off the platform.



TaskRabbit was a generalized marketplace without category constraints on supply. This put a burden of complexity onto its buyers. A positive review of someone who cleans your house has little relevance if the next buyer wants to hire that person to assemble a desk.

6. Gig economy verticals follow a power law

In today’s gig economy landscape, the ridesharing category rises above every other vertical combined, followed by restaurant delivery and grocery delivery.



Today’s most successful players recognized early on that power law governed verticals. Postmates, for example, started as a generalized delivery service but rapidly pivoted into focusing exclusively on restaurant delivery after realizing that that was the bulk of their requests.



Of all the lessons on this list, this is perhaps the biggest one that TaskRabbit failed to learn in time. As each vertical got successively dominated, TaskRabbit stuck to a general marketplace model and refused to pivot into any specific domain.



By the time the company finally refocused in 2014, many of the most compelling verticals were already too crowded. TaskRabbit had to settle on house cleaning, moving, handywork and personal assistants -- all infrequent use cases that limited marketplace growth and monetization.

Hindsight being 20/20, it’s easy to look back on the history of TaskRabbit and see missed opportunities. With its first move advantage, it’s easy to imagine that it could have been TaskRabbit that became the dominant global ridesharing company on its way to a $100B valuation.



But, while TaskRabbit was remarkably prescient about what the gig economy was going to become, a few key decisions and mistakes around marketplace growth blocked it from successes that its later competitors enjoyed. Still, it’s worth taking a moment to appreciate the groundwork TaskRabbit laid for the successor companies that now touch our lives every day.



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