Analytics for Product Managers
by Lauren Sperber on May 10, 2010
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video here: http://vimeo.com/11658073
video here: http://vimeo.com/11658073
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* how analytics can guide PMs
* data points you may need as a PM
* tools and techniques for getting that data
* OI elevator pitch
* anecdote about how widely the role can vary
* in all but one of these bullet points I’ve had the title product manager
* 1st pm: organization, prioritization of competing projects, and process for product planning and development
* one-woman product team
* operational role: creating traffic and revenue projections and directing strategy for content acquisition
* one of two specialized PMs reporting to new VP of Product
* focus on content analysis, data integrity, search rankings, and our unreleased API
* no PM is at either extreme
* since this talk is so data-focused want to point out that there are a variety of degrees to which data will play a role in different projects
* data is a sounding board
* in a situation where you feel like you don’t have data --> use your creativity to find some
* use your instincts and understanding of your product to guide your interpretation of any data
* PMs make tough decisions about how to spend our time and developers’ time
* these debates are always going to be rife with politics and emotions
* numbers or even the promise of numbers to the table can help you be a voice of clarity and direction
* e.g.: OI built a simple A/B testing platform prior to our redesign and the promise of data-driven decisions helped to diffuse tension over how aggressively to change the site
* tracking succes
* e.g.: OI tracked change from text link to graphic button-->clicks went up--> clicks went down--> sometimes change makes people click
* numbers don't prevent subjectivity, guarantee success, or help you win every argument
* prioritize --> make a decision based on the key value propositions of your product
* if you can't control your stats, you may not be optimizing for the right metric for your product or the age of your product
* e.g. tracking PVs/visit on OI is frustrating, because it currently has a very simple value proposition: to get users to content they care about. instead we track clicks to third-party content per visit, which is more central to our value proposition
* DM: acquisition, activation, retention, referral, revenue
* +1 to FW’s notion that metrics have to change and be specific to biz/product
* DM calls out really specific terms that clarify the mystery behind some of the more general terms
* I’m going to cite four buckets of analytics (in general terms) and clarify the spirit behind them
* consumer website: unique visitors
* desktop/mobile app or subscription service: downloads/signups
* publishing tools: like Twitter or Tumblr or Outside.in for Publishers
* pub tools: DLs/signups + uniques on your users’ content
* promise behind it is like that of the engagement ring: how much people love your product and how loyal they’ll be
* conversion should measure what you hope you’re giving users
* choose an engagement metric that exposes the main value proposition that your product makes for users
* e.g. pageviews/visit versus clicks per visit for OI
* typical: PVs/visit, time on site, bounce rate, return visitors, logged-in sessions
* for pub tools: on your users content
* generally: how frequently people do a specific thing that you want
* account registration
* upgrade
* providing info
* OI e.g.: clicks on ads as conversion
* other analytics should drive revenue
* some companies have a mandate from investors to focus on building a product they love, but it's important to keep the spectre of revenue and how you'll track it in mind while you build your product
* ads can be paid on CPM (flat rate per thousand impressions), cost per click, or cost per action
* subscription or license feeds
* one-time purchases
* BizDev deals like foursquare’s deals with bravo and the history channel
* most of these can be boiled down to: think like a hacker about where you can cram variables into your tracking tool and add as many as possible
* suck it up and hack GA
==campaign trackers==
* campaign trackers page is written for people tracking the success of ad campaigns
* just a bunch of query strings that you can define any value for (utm_content, utm_campaign, utm_medium
* in twitter’s emails
* track clicks in the “campaigns” view under “traffic sources”
==detailed paths and title tags==
* analytics “content” view lets you filter types of pages by info in the URL paths or title tags
* make sure they have as much info as possible, but optimize your identifying strings for search queries because paths and titles are important to SEO
==goals==
* set up goals for engagement or conversion tracking
* multi-step conversions create funnel visualizations
* if you want to use funnels, make sure each step of your conversion process has a unique URL (variables ok, just use head match or regular expression)
* see the results in the funnels section under goals
* shows where users are coming from to enter your conversion process, how many proceed, and where they drop off
* identify steps in conversion that need usability testing or distracting links along the way
* diagram that shows what pages users are coming from to reach the first step in your conversion process
* for each step, how many proceed to the next step and how many drop off
* shows how many drop offs go where
* identify pain points for usability testing
* identify distracting links
* Google’s Website Optimizer can set up simple a/b tests for static landing pages
* OI built a simple a/b testing tool that sets a number between 0-1 in the session and compares it to the % of visitors we want to show each template
* make sure you can get every KPI for your product in both templates
* a change you make for engagement could negatively affect monetization
* have a token representing the template you’re testing in your title tag for analytics, in your ad tags for revenue monetization, in your campaign URL trackers for conversion or engagement
* sign up for a Quantcast account --> greater accuracy + privacy settings
* labels let you add a string you define 3x in your tracking code
* labelled traffic shows up in “audience segments” in your Quantcast profile (can be made private)
* use labels to segment your traffic however makes sense
* OI uses these to measure which users of our publisher dashboard users are generating the most reach and traffic
* don’t waste your time trying to reconcile them perfectly, but choose a package to be authoritative. this should be the numbers that pay you.
* be on the lookout for dramatic differences as a heads-up that something is awry
* OI found that Analytics was reporting 200% fewer visitors and pageviews than Quantcast for the widgets distributed by users of our self-service publishing product
* ad server, Google Ad Manager (which doesn’t track reach) roughly agreed with Quantcast on the pageviews
* no discrepancy for our main site
* hack for tracking JS widgets on other domains --> wrote in iframe that called a source page on our domain w/tracking code for GA + Quantcast and ad tags for Ad Manager
* Google Analytics could not track a large portion of visits made in IE via this hack but Quantcast and AdManager code didn't have that discrepancy
* AdManager numbers were luckily the highest of the bunch
* conversion metrics should play to the key value you want to GET from users
* learn how your analytics package works and cram as many details into it as possible
* twitter
* neglected blog