{"pageProps":{"posts":[{"post_information":"{\"title\":\"Monitoring a Feature Launch with SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"inspect\",\"author\":\"Bill Babeaux\"}","slug":"monitoring-a-feature-launch-with-sql","id":"product","position":0,"isDraft":false},{"post_information":"{\"title\":\"Auditing a Customer's Usage of Your Product\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"inspect\",\"author\":\"Bill Babeaux\"}","slug":"how-has-customer-used-your-product","id":"product","position":1,"isDraft":false},{"post_information":"{\"title\":\"Ranking the Most Used Features in Your Product\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"inspect\",\"author\":\"Bill Babeaux\"}","slug":"product-most-used-features","id":"product","position":2,"isDraft":false},{"post_information":"{\"title\":\"Finding Your Product's Most Engaged Users\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"inspect\",\"author\":\"Bill Babeaux\"}","slug":"finding-your-most-engaged-users","id":"product","position":3,"isDraft":false},{"post_information":"{\"title\":\"Filtering Users by Version Number with Regex in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"schema\",\"author\":\"Bill Babeaux\"}","slug":"filtering-users-by-version-number-with-sql-regex","id":"engineering","position":4,"isDraft":false},{"post_information":"{\"title\":\"Filtering Users by Platform in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"schema\",\"author\":\"Bill Babeaux\"}","slug":"filtering-users-by-platform-in-sql","id":"engineering","position":5,"isDraft":false},{"post_information":"{\"title\":\"Calculating Daily Active Users (and digging deeper)\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"announce\",\"author\":\"Bill Babeaux\"}","slug":"calculating-daily-active-users-in-sql","id":"marketing","position":6,"isDraft":false},{"post_information":"{\"title\":\"Analyzing NPS Responses in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"troubleshooting\",\"author\":\"Bill Babeaux\"}","slug":"analyzing-nps-responses-in-sql","id":"support","position":7,"isDraft":false},{"post_information":"{\"title\":\"Finding Customers at Risk of Churning\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"troubleshooting\",\"author\":\"Bill Babeaux\"}","slug":"finding-customers-at-risk-of-churning","id":"support","position":8,"isDraft":false},{"post_information":"{\"title\":\"Detecting Spikes in Issues from Support Tickets\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"troubleshooting\",\"author\":\"Bill Babeaux\"}","slug":"detecting-spikes-in-issues-from-support-tickets","id":"support","position":9,"isDraft":false},{"post_information":"{\"title\":\"Tagging Sign Up Emails as Work vs Personal\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"grow\",\"author\":\"Bill Babeaux\"}","slug":"tagging-sign-up-emails-as-work-vs-personal","id":"sales","position":10,"isDraft":false},{"post_information":"{\"title\":\"Creating Lead Scores in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"grow\",\"author\":\"Bill Babeaux\"}","slug":"creating-lead-scores-in-sql","id":"sales","position":11,"isDraft":false},{"post_information":"{\"title\":\"Running a Funnel Analysis in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"announce\",\"author\":\"Bill Babeaux\"}","slug":"running-a-funnel-analysis","id":"marketing","position":12,"isDraft":false},{"post_information":"{\"title\":\"Marketing Attribution in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"announce\",\"author\":\"Bill Babeaux\"}","slug":"marketing-attribution-in-sql","id":"marketing","position":13,"isDraft":false},{"post_information":"{\"title\":\"Creating Histograms in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"analyze\",\"author\":\"Bill Babeaux\"}","slug":"how-to-create-histograms-in-sql","id":"analytics","position":15,"isDraft":false},{"post_information":"{\"title\":\"Detecting Skewness in a Dataset in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"analyze\",\"author\":\"Bill Babeaux\"}","slug":"detecting-skewness-in-sql","id":"analytics","position":16,"isDraft":false},{"post_information":"{\"title\":\"Calculating Linear Regression in SQL\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"analyze\",\"author\":\"Bill Babeaux\"}","slug":"linear-regression-in-sql","id":"analytics","position":17,"isDraft":false},{"post_information":"{\"title\":\"Exploring our Sample Dataset\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"analyze\",\"author\":\"Bill Babeaux\"}","slug":"exploring-sample-dataset","id":"analytics","position":18,"isDraft":false}],"data":"{\"content\":\"![](/static/images/templates/covers/cover_work_vs_personal.png)\\n\\nSay you’re building a B2B product. A lead who signs up with a corporate email is more likely a qualified buyer.\\n\\nOf course, email type is not the only signal (see our template on [Lead Scoring](/sql-templates/sales/creating-lead-scores-in-sql)). Once you've baked all your signals into a Lead Score, you can even pull a daily report of [Recent Qualified Leads](/sql-templates/sales/creating-lead-scores-in-sql).\\n\\n## Why SQL?\\nSQL is fast and flexible. You can write a `CASE` statement in a snap, no data instrumentation or JIRA tickets required.\\n\\n\\n## SQL you can copy / paste\\nUse this query on any `users` table ( ⚠️  if your table is massive, filter by `created_at`).\\n\\n```sql\\nselect\\n id,\\n first_name,\\n last_name,\\n email,\\n case\\n   when email similar to '%(gmail|yahoo|outlook|hotmail)%' then 'personal' --simplified list\\n   else 'business'\\n end as email_type\\nfrom users;\\n```\\n**Sample Output:**\\n```\\n| id     | first_name | last_name | email                | email_type |\\n|--------|------------|-----------|----------------------|------------|\\n| 538107 | Aaliyah    | Funk      | aaliyah@craftery.com | business   |\\n| 471400 | Abbey      | Miller    | abbey@weavel.com     | business   |\\n| 565108 | Cheyenne   | Reilly    | cheyenne@hotmail.com | personal   |\\n| ...    | ...        | ...       | ...                  | ...        |\\n```\\n\\nObviously that list of email domains is simplified to make the concept easy. Here’s a <a href=\\\"https://gist.github.com/tbrianjones/5992856/\\\" target=\\\"_blank\\\">full list of domain names</a> that we consider personal (or burner).\\n\\nTo easily paste that list into your query, use <a href=\\\"https://delim.co/\\\" target=\\\"_blank\\\">delim.co</a>, choose `|` as the delimiter, and then paste into your query like so:\\n![](/static/images/templates/personal_emails_to_delim_to_popsql.mp4)\\n\\n## Try it yourself?\\nRun this template against our [sample database](/sql-templates/analytics/exploring-sample-dataset) that mirrors real startup data. See the [connection credentials](/sql-templates/analytics/exploring-sample-dataset#accessing-this-database), then connect in PopSQL.\\n\",\"data\":{\"title\":\"Tagging Sign Up Emails as Work vs Personal\",\"date\":\"2020-07-30T00:00:00.000Z\",\"draft\":false,\"icon\":\"grow\",\"author\":\"Bill 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