Glovo Strategy
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hdl:2117/357242
CovenanteeGlovo
Document typeMaster thesis
Date2021-07-13
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Abstract
Glovo is a start-up based in Barcelona, which’s aim is to give everybody access to anything in their cities. It is an on-demand delivery platform, offering food, groceries, gift shops and much more, all through the same platform. One of the major problems the company is facing is the retention of Partners (the stores that offer their services in the app and so, have signed a contract with Glovo). This is mainly driven by Partners who don’t receive orders and so are in danger of leaving the company, as well as Partners that have already left and no longer work with Glovo. The mission of this project then, is to help with the Partner retention by analyzing the metrics and factors that drive our Partners to churn and receive zero orders, as well as understanding our Partners performance; how they are doing in terms of orders, how are the orders distributed and what level of orders might be keeping our Partners perform better. We have found that new and existing Partners are not getting enough exposure in the app; 53% of Partners receive from 0 to 25 orders/month & they lack transparency into how to affect their ranking, which means that they don’t know which metrics are the ones affecting the way Partners are sorted in the app, or which criteria does the sorting follows. On top of that, Glovo’s GMV (gross margin value) is heavily concentrated into a few Partners. Firstly, it is important that Partners receive more orders, since orders are directly correlated to impressions (each time a store has appeared in the customer’s screen when looking into the Glovo app). So, there is a need of giving new and unhealthy Partners (Partners receiving zero orders) more visibility through the app. Therefore, we defined new metrics in order to change the way Partners are sorted in the app, to let impressions be more distributed. As well, offering better experiences to users by improving the Partners performance KPIs (waiting and delivery time etc.) is directly correlated to more orders received. Secondly, we are going to define an activity funnel to classify all the Partners that are not being visible in the app, connected, or having orders, in order to give them specific communications to try and convert them into active Partners (receiving orders or connecting to the app)
SubjectsElectronic commerce -- Mathematical models, Affiliate programs (World Wide Web) -- Marketing, Express service -- Barcelona (Spain) -- Management -- Marketing, Comerç electrònic -- Models matemàtics, Programes d'afiliats (Web) -- Màrqueting, Transport urgent -- Barcelona (Catalunya) -- Administració -- Màrqueting
DegreeMÀSTER UNIVERSITARI EN ENGINYERIA INDUSTRIAL (Pla 2014)
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