Thread
#discussion
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    fierce-school-97248

    5 months ago
    One of the larger pieces of news out of the data world in the last few months was the layoff of Looker's entire US-based support team - the Department of Customer Love. As a long time user of Looker at many organizations, let me tell you that their CS was one of the top teams out there, with a great UI experience - simply hit the button, start talking to a rep, and with a bit of effort get your problem solved reasonably fast. It's almost unheard of for companies with Looker's scale. This has got me thinking - the UX in Looker is "Hit a Button" -> Get a Looker CS Rep on the line -> work through the problem. Data people do this, and end users (dashboard consumers/business stakeholders) as well. Given Looker's divestment in this CS team - what would the ideal experience look like for end users to "Hit the Button" and instead of this going out to Looker, to be routed to the data team? Right now, it's a slew of Slack messages, one off DMs, etc. It's not manageable at scale. What is the ideal UX here and how can tools like Secoda support? I think most of the features are there, just curious about how people may have tried this, especially at enterprise and larger customers. Curious if anyone has wins or stories.
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    limited-solstice-12595

    5 months ago
    I think that @hundreds-artist-88428 might be able to shed some light on this and how his team is using the product. The “ask a question” feature is used quite a bit at Partnerstack
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    hundreds-artist-88428

    5 months ago
    i’ll send over the documented process we use
    basically it’s like a ticketing system that’s integrated with slack, that we review every morning as a team, and asign the questions
    that way it is manageable / doesn’t get overwhelming
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    limited-solstice-12595

    5 months ago
    @hundreds-artist-88428 how does your team about SLA’s? Do you share what the expected response / solve time is for a ticket?
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    hundreds-artist-88428

    5 months ago
    we say within a week
    but we average around 4.5 days
    some questions we had hanging for several months tho lol
    some get answered same day
    all depends on if the data is readily available or not
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    limited-solstice-12595

    5 months ago
    Makes sense