Helpshift Tutorials - Analytics


Digital customer service platform and ticketing system

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Helpshift Tutorials - Analytics

Video Transcript

Speakers in this video: Jimmy (GetApp) and Adam (Helpshift)

Adam: Now, we also have our analytics page as well. This is easily accessible. This gives you a high level overview of what’s going on in the dashboard in the account. Obviously this is a demo app so the data isn’t quite as extensive. But it gives you a rough idea on what you can track at the highest level. Keep in mind if you are a big data organization, if you have your own business intelligent person, a data scientist on your team you can get Amazon S3 down raw data files that you can compile or excel or whatever to get your own custom KPIs and metrics.

We’ve found most of the poor organizations just want to see certain KPIs to see if they’re doing well. Tags are really important. Tags understand what the issue is and what the user type is. You can set these up to be created automatically. Remember we’re an STK so we know everything about your user so when it’s passed through we’re automatically tagging it based on rules you set. You’re going to identify a new user maybe a new user to you is someone who has less than seven app sessions and has made less than two purchases if you’re a shopping app. You can also do an issue type. Maybe it’s a bug or maybe it’s feedback and you want to route it a certain way.

In the analytic section when you’re going over tags you want to see what’s coming in this week or last month or last three months. We can download reports here. This gives you an idea of what’s going on or a lot of the users contacting me or a lot of my VIP users or am I seeing a lot of bugs? Am I seeing a lot of issues regarding payments? It gives you a great opportunity to show data to your product team to make those changes to make your product better because at the end of the day Help Shift wants to make it really easy for your team to make your product better for your users and keep those users using your product and of course gain more users.

Help Shift’s really great about self-service as I mentioned before. We’re actually tracking who’s being self-served and how many fewer tickets are being submitted because we’ve shown fewer vast amount of customers and data points that self-service stuff likes up to 95% of tickets. People want to self-serve. With Help Shift if you’re coming over from a different help desk a traditional help desk you will actually need fewer agents and that’s purely because our FAQs are so good that it’s replacing the work of many agents.

As you can see here user engagement how many times someone’s opened up help, how many FAQs are read and how many are reported issues. Now of course this data isn’t that accurate but you’ll see most of the time like I mentioned 95 percentile in terms of self-service. You can see at the highest level how many active users you have in a given week. You can go by app platform your contact rate as well. How many active users are actually contacting filing an issue; issue reported, issue resolved, time of first response and then time to resolve.

"Now you can even deep dive as well into specific issues. Here we’re going to deep dive and you’re going to plot a graph. You can show different metrics. I’m going to show you really fast what we’re tracking – reported, resolve, the backlog. We have a survey rating as well so after each conversation is resolved the n user can rate the level of service that the agent provided. If you’re using a traditional email based Help Desk, this comes as a follow up email to the user. Maybe it’s an hour. Maybe it’s a few minutes. Maybe it’s the next day. The response rate on that is horrible. We’re talking less than 10% quite often it’s in the three or four percentile because that’s email within that because it’s immediate because it’s just like lifting Uber when you’re done with your ride. We’re actually getting much higher response rates.

""You can see here and really gage your agents. Are they doing well? Do I need to make this agent promote them? Do I need to demote them? Really understand as well is when you get some more outsourcing partners. Are these agents performing well? And which outsourcing teams are performing better or worse than others?

Response rate is actually responding to issues coming from the dashboard of the user, acceptance rate. At the end of each conversation users mark it with a question. Did we answer all your questions, yes or no? We’re actually empowering the user to end the conversation which in today’s world is what users expect. Users have the power. That’s what you’ve seen with social media, with app engagement a user feels control of what they like. It is much better for customer satisfaction where if you’re an agent and you give them good answers. They will mark it ‘yes’ and you will get a higher rating or if for some reason they click ‘no’ they can submit a new reply back and you can prioritize that ticket and make sure that their questions are actually being resolved appropriately with the correct answer, time to first response, holding time, average time to resolve, median time to resolve, reopen, reopen rate, first contact rate (FCR Rate) this is really important too.

We have automations that run after a new issue has filed and a lot of times those are answers to questions. It’s measuring how many of those new issues are being resolved with just one touch which of course makes it more efficient as a team and gives a better user experience. You can also measure FAQ trends as well. Are FAQs being read? Are they liked, disliked? I mentioned this earlier.

Another great thing about Help Shift is the data we collect. We call this custom Meta data. The ... developer sets up one time at the STK level and you can pass through any piece of data you’re already tracking about your user into the dashboard. The idea here is that you want to see data that an agent doesn’t have to go look up or do a sequel query or look up a different system, define it and then copy and paste it over. There are actual data. It’s their funds and you can act upon it. Data examples include: number of orders placed, the LTB of the user. Are they a new user? When was the last registration date? Anything that makes you more efficient and so you can be able to prioritize and segment your users and assign the appropriate help when needed.

This is how we’ll look like in the dashboard. I go here and a ticket you can view more. Right here user type is paid. You can see here I can do hs-tags, also device information as well. Remember we’re an STK. So a lot of times you can eliminate bugs or other technical issues just by seeing accurate device information. This is in comparison to what’s currently out in the market with email. With the email, if you have a bug and the mobile app is using email as the main method of communication and the user writes to them: “Hey I’m seeing a lot of crashes”. First question that the supporter’s going to ask is. What’s the device you’re using? What’s the operated system? How much memory do you have? All these questions and if you’re a person who’s not very technical or you don’t want to go look it up you can copy and paste that, you’re just going to churn. You’re going to say “I don’t have time to deal with this. I’m going to go get a new app.”

With Help Shift because we’re in STK it’s accurate data, automatically rendered to support agents to resolve these kinds of technical issues so it’s smart. It’s a much better experience and we’re seeing that with our customers who migrated over from these email based Help Desk to Help Shift and seeing a lot more efficiency and less issues about bugs and crashes. We’re able to supply debug logs as well so you can really deep dive into any technical issues as well."""