Building Lyft’s Marketing Automation Platform | Hacker News Reader

Building Lyft’s Marketing Automation Platform

eng.lyft.com

109 pointsryan_lane13 comments

Netflix has written about their internal platform as well[1].

Has anyone come across other articles similar to these? I haven't been able to find many outside of these two.

1 - https://medium.com/netflix-techblog/engineering-to-improve-m...

I tried to become a driver, but my license plate is not from the state that I currently reside in, so I fell thru the cracks and now I am stuck in this funnel with no way out.

Every once and a while I get an obscure request from Lyft and I can't immediately tell if it's related to my identity as a rider or my identity as a driver.

Wish all of these marketing funnels had a big "PULL CHUTE" button so that users can remove themselves. I'm stuck in a hundred car dealership funnels too, and continue to get "nurtured" week after week.

> I'm stuck in a hundred car dealership funnels too, and continue to get "nurtured" week after week.

Do you mean being a driver for car dealerships for delivery and dropoffs? What does nurtured mean exactly?

They’re in the marketing funnel, because at one point in the past they were in the market to buy a car, and still receive VERY frequent messages encouraging thrm to continue down the sales process despite the fact they didn’t engage with any previous marketing message and bought a car years ago.

Really curious to know more about how Lyft handles attribution here as I didn't really see it mentioned. Nor did I see much about how they approach view through metrics for display and such when that data is increasingly locked away within the ad platforms and not always exposed via API. Presumably things are mashed together in an ad server and some enterprise analytics platform with an attribution tool in the mix, perhaps with a sprinkling of MMM.

Beyond that, I'd love a deeper analysis of their actual channels and how they measure and approach them. Any additional links on that would be much appreciated.

Wonder if this is related to the thing where Lyft spams people with phone notifications that are really just ads/promos, and then continuing to do it for multiple years.

https://twitter.com/asklyft/status/634509838358302722?lang=e...

Are there any good products to help do this sort of thing?

It seems to me there would be lots of integration to do between the LTV predicator and quite a few other systems, so this would need quite a large team to make.

Maybe I'm wrong...

There are products that solve different parts of this problem, but most companies buy 2-4 products for their marketing stack (CDP, Marketing Automation, attribution, and analytics). For things like LTV prediction, you would either need to buy an additional piece of software or do it yourself.

Each company does marketing enough differently that there isn't a single product that could solve the problem end-to-end for everyone.

Full disclosure : I work at the company mentioned below

There are products out there like this. There are emerging tools like Syntasa (https://www.syntasa.com/) that have all of these integrations baked in to allow you to grab exact same data from various SaaS tools you are using (like Analytics, Marketing automation etc) and have templates for various analytics activities like attribution or LTV or propensity modeling and integration points back to activation points in your Marketing stack. This allows you to perform many advanced analytics activities, customize it for your business without needing to hire a very large team. In fact, even large teams find it more useful to use a tool like that so they can spend their time worrying about their objectives instead of spending months gluing everything together.

Like OP mentioned, CDPs and Marketing automation are glue tools in a way but they have superficial data and are not meant for in-depth analysis.

Would be cool to see an actual demo. Sounds pretty amazing but I wonder how automated the process is.

Fun post about efficiency from a company that is chronically loosing money.

Sad to see all of this engineering effort being spent on spreading cancer (aka ads) and thus funding worldwide stalking by unethical companies.

Just imagine what humanity could’ve achieved if efforts like these were directed to actually worthwhile causes like science or medical research.

I used to think like this before. But then I realized the survival of these companies (similar to natural selection) is based on these efforts which makes it almost the exact opposite of cancer.

To a customer, if the value add is ride sharing to exist in some form, companies actively bidding for that customer's attention and eventually their pockets is inevitable.

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