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Marketplace Management Insights in Looker
- 2. Winfred Peereboom CTO - Werkspot
- 3. add photo here Werkspot ● Founded in 2005 ● Moved to Amsterdam in 2012 ● 120+ Employees (Hiring!) ● Using Looker since 2015
- 5. Our mission “Be the easiest and most reliable way to arrange home services.”
- 6. add screenshot here (375 x 667) add screenshot here (375 x 667) Our product - marketplace for homeservices Professionals “We need our TV configured” “We are looking for a mover” “Who can paint my walls? ” Consumers “Friday I am available” “We help you move from A to B” “Let us help you!”
- 8. Overview
- 9. Sources ● Product data stored in MySql ● Product events of actions in the product ● Target settings stored in Sheets of Sales ● Mail events from Mandrill ● Analytical data from Google Analytics ● Advertisement of Bing/Facebook/Adwords ● Salesforce CRM
- 10. SqlRunner: An executor of SQL files in parallel or sequel order. Lambda: Scripting data from S3 and SQL for storage in different formats. Looker PDT: Materialised views for giving period of time. Data transformation Playbook: Execute ordered SQL queries Only SQL: No scripting functionality Serverless: Utilising AWS Maintenance: Git/Monitoring/CI/CD Integration: Combined with the data usage Dependencies: Explores depending on multiple PDT’s
- 12. Goal of a marketplace Process as much delivered Gross Merchandise Volume as possible for a fair take rate.
- 13. Balancing supply & demand SupplyDemand Consumer Service professional
- 14. Services 1 Plastering wall or ceiling constructions 2 Pave outdoor and garden 3 Interior painting 4 Bathroom renovation 5 Exterior painting 6 Wall or floor tiling 7 Create garden 8 Replace or renovate roof 9 Install fence 10 Install laminate floor Services : 225+ Professions : 30 Services : 170+ Professions : 21
- 15. Location Mountains and Islands - IT Surfaceareas IT 300.0 00 km2 NL 40.00 2 Sunny Italy, demand for HVAC Swimming pools in NL
- 16. Service Location combinations More demand than supply Low consumer NPS High SP NPS Undersupply Too low liquidity Bathroom renovation in Utrecht Add SPs Stop SR acquisition Healthy trade-off supply/demand High consumer NPS High SP NPS Balanced Desired situation Exterior Painting in Zuid-Holland Maintain balance More supply than demand High consumer NPS Low SP NPS Oversupply Too high liquidity Interior Painting in Noord- Holland Add SRs Deprioritize in sales
- 17. MM in Looker
- 18. Distribution of services Italy
- 19. Automated adjustments Advertisement costs Get underperforming campaigns: Based on the verdict we retrieve the underperforming campaigns. Adjust bidding or stop campaigns: Based on the verdict we tell Google Adwords to change the bidding or stop the campaigns currently running.
- 20. Automated adjustments Onboarding experience Get oversupply services: Based on the verdict we know what services are having enough Service Professionals. Block sign up for specific services: Based on oversupply we put Service Professionals on a waiting list before activating them in to respond to certain services.
- 21. Explore the Requests Underperforming due to multiple service request. Fix: Split the job
- 22. Customer Service Resending notifications Get underperforming Service Request: Improve the quality of the service request to get more interest of the Professionals Inform Professionals : Let the service Professionals know there is an interesting job for them, or with improved information to respond on.
- 24. Account management Cold calling new Professionals Low competition services Look for services where the number of Professionals is low. Invite Professionals : Account manager will contact the Professional and will invite him to join for free to respond to service requests.
- 25. Benefits & Learnings ● Verdict model is enabling us to better support our customers. ● ETL and data definitions are most of the work. ● Everything integrated is preventing from having Excel sheets ● Looker users can get more insight by exploring data VS static reports. ● Verdict model is a competitive advantage.
Editor's Notes
- Founded in 2005 Moved to Amsterdam in 2012 120+ Employees (Hiring!) Using Looker since 2015
- We are active in 5 countries in Europe, United Kingdom, Germany, France, Italy and the Netherlands. Our mother company HomeAdvisor is active in the US.
- Our mission is to: Be the easiest and most reliable way to arrange home services. This sounds nice, but what does this mean?
- Our product is about having a marketplace for Consumers that are in need of a certain service, looking for example for a painter, mover or handyman. On the other hand Service Professionals that are available and looking for work.
- We simplified everything this year and are using Stitch for data extraction, Snowplow for event collection and we store the data in Redshift. With Looker we are building reports and Dashboard to explore the data.
- We are having multiple sources of data that we would like to see combined in our reporting tool. We gather data from: Product data stored in MySql Product events of actions in the product Target settings stored in Sheets of Sales Mail events from Mandrill Analytical data from Google Analytics Advertisement of Bing/Facebook/Adwords Salesforce CRM
- After we loaded all the data in Redshift we have 3 ways for transforming the data the best way so it can be consumed by Looker. First we have the SQL runner that is part of Snowplow. After events are processed and stored in Raw format we execute a playbook of SQL queries. Advantage here is that it’s just SQL and pretty easy to read, but it’s missing the real scripting options. Lambda is helping us out on this, where we can script SQL and data in different formats to be transformed stored into redshift. These first two options are costing quit some maintenance and effort to control with Monitoring and deployment, especially when the amount of jobs is growing. Also Looker is providing a way to Transform data and prepare to consume. So called Persistent Derived Tables, also known by Materialised views. This is similar as the SQL runner only more focused on the actual data that will be used by the reports and dashboards available in Looker and thereby often faster. A downside of this approach is that these persistent derived tables can be depending on other PDT’s that needs be regenerated to prevent using “outdated” data.
- Now I will dive deeper into the world of a marketplace like Werkspot.
- Goal of a marketplace is to process as much delivered gross volume as possible for a fair take rate. Probably for people not active in the world of marketplaces there are couple unknown concepts. The delivered Gross Merchandise Volume is the money/volume that is being processed through the platform. For example at marktplaats.nl this will be the sum of prices of all sold goods or services via marktplaats.nl. For us it’s the sum of money Service Professionals get from the jobs they execute via our platform. Our business model is to ask a fair amount of money based on what the Service Professionals are receiving or what we expect them to receive.
- So with a marketplace it’s about the balance between Demand and Supply, there should be enough supply of Service Professionals that are available, but also enough jobs that needs to be done for the Service Professionals. This balance is at Werkspot our biggest challenge. This is so challenging because:
- First of all we try to serve a broad range of services and thereby a broad range of professions. In The Netherlands we are active in more than 225 services and for Italy more than 170. This is covered by 30 professions.
- Not only the balance is different per service also highly influenced by the location and thereby traveltime of a Service Professional. A couple examples, like all the water in the Netherlands is allowing Service Professionals only to drive long distances for big jobs to in the Netherlands. Similar in Italy when there are mountains and Islands it’s blocking Service Professionals to serve all consumers. It’s also warmer in Italy and thereby the need for air conditioning is much higher compared to the Netherlands.
- So what we try to do is to create Service Location combinations and figure out how the balance is and label these categories with Undersupply where there are not sufficient Service Professionals to fulfil all needs. Balanced if it seems to be fine and oversupply if there are more Service Professionals available than there is actually work available. As it can be expected this will result in a low Net Promoter Score for either the Consumer when there is undersupply and for an Service Professional when there is to much competition in an oversupply area.
- Because we have so many services and locations we are currently using Looker for marketplace management. Looker is a tool comparable to Tablau, Power BI, Qlikview and others.
- Here you see a screen shot from Looker that is showing the distribution per service for Italy. So if you look to the top row, 21% of the Requests from a consumer for Home Renovation doesn’t have enough Service Professionals, 28% is ok and 50% Is covered by tho many Service Professionals. Thinking about this, this might be due to the reason it’s quit a step to have your house renovated, so maybe not so much requests. Other reason could be that the order value per request is high and thereby more interesting for a Service Professional to drive longer distances. So what can we do with this data insights?
- To get more Service requests in we are using mainly Google Adwords. With an API integration we get the underperforming campaigns and adjust bidding to target better for better conversion from Ad -> posting a service request in our platform.
- When we already have to much Service Professionals for a certain profession in a certain region, we create a waiting list for sign ups. With the current positive economy this is almost nowhere the case, only the painters in A’dam might be a little too much.
- With Looker we can also dive deeper into the balance situation, we often see that consumers are posting one request but are in need of multiple Service Professionals. In this example to do some laminate flooring and painting job. Our customer service will follow up on this and split the job and help the consumer to find the right service professional
- When there is undersupply we will try to invite more Service Professionals to make a proposal for executing the job. We do this by resending an improved request to a more specific group of Professionals.
- Like earlier said, we are in need of more Service Professionals in specific services. This will give clear directions to our sales team.
- So when there is low competition for certain services, our account management team invite new professionals and tell them that they can get some work via the platform.
- So what are our benefits and what did we learned from having a marketplace management model. Verdict model is enabling us to better support our customers. ETL and data definitions are most of the work. Integration prevent having Excel sheets with personal data. Looker users can get more insight by exploring data VS static reports. The verdict model is a competitive advantage. although I know told you how it’;s working ;)