How to Tap Into Latent User Demand in a Marketplace

Ankur Sharma

Chief Product & Technology Officer (CPTO) at Perkbox


Finding New Areas of Growth

When you are already the largest e-commerce player in the market, it is always a challenge to find new areas to grow. This is what happened with us when Goibibo was already the largest B2C player in the Hotel industry. It was difficult to find the next feature or product to build, seeing that we already faced many successes.

Using Customer Latency

We built “Hourly Bookings” to drive growth in the TG of business travelers, pilgrimage, and transit hyper-locations. This helped us cater to the latent demand of users who only wanted hotels for a few hours and not for the whole day.

Using the rigor of daily data observations, when we triangulated quantitative data (funnel, increase in transactions happening at specific cities like Pilgrimage & hyper-locations like airports and train stations) and qualitative data (Focus Group Discussion, surveys of people who dropped off the funnel at payment at these cities and hyper-location in the advanced purchase window of 0 to 3)
, it dawned on us that we are on to something. We realized that there is a user need for a product where a user can stay for less than 1 room a night, which was not offered by any Online Travel Marketplace at that time.

We identified customer needs and target locations as:

  1. Pilgrimage travelers: Many pilgrimage travelers look for a 3, 6 hours stay for a fresh-up before and/or after the pilgrimage activity in the town.
  2. Transit Travellers: Need at a transit hyper-location like Airport, Bus-stand and Railway stations where the customer may need a room before the boarding / after the de-boarding.
  3. Highways: Traveller may need a 1 to 3 hours break during the long road trip.
  4. Four and Five Star Hotels: This use case will serve the need of the leisure traveler who wants to avail luxury hotel amenities like pool, lounge, spa, etc. by paying a lot lesser.

On the supply side of the marketplace, we spoke to sellers (in this case, hoteliers) (and identified hoteliers’ objectives as

  1. Liquidate unsold inventory
  2. Capture online demand for micro stays

We first ran a proof of concept in a specific geography with 11 hotels and a soft launch on the web at a pilgrimage location. Success Metrics for the POC were:

  1. Higher transaction and GMV for the participating hotels
  2. Higher Occupancy Rate for Hotels
  3. Higher conversion rate than funnel (because of lower ATV)
  4. Incremental transactions 

The POC execution helped us in identifying what works (successful in driving the higher occupancy rates, better conversion and incremental transactions) and what needs to be improved upon (Better visibility at the top of the funnel, flexible slot timings and pricing) - we arrived at a playbook for supply to roll this out in multiple cities and scale this simultaneously in the funnel.

Using the playbook, we could quickly scale the hourly bookings product in 300 hotels in 9 cities, bringing in 2.5% incremental transactions per day at a higher conversion rate than the funnel. This taught us the massive value of building a playbook as well as keeping an eye on new trends by triangulating the data.

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Ankur Sharma

Chief Product & Technology Officer (CPTO) at Perkbox

Leadership DevelopmentCommunicationOrganizational StrategyDecision MakingCulture DevelopmentPerformance MetricsEmerging TechnologiesCareer GrowthCareer ProgressionSkill Development

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