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Summary

It's now possible for anyone in the revenue org to write health scores that actually meet their business needs in a matter of minutes. In this video, I demonstrate how, Delegate, empowers Revenue Org members to create customized components for customer insights swiftly. By leveraging frontline intuition and machine learning signals, we can now easily analyze customer data and revenue impact. I showcase the process of creating a component to track SLAs in our support tool and its seamless integration with our sales CRM.

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Why you should watch?

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If you work in #RevenueOperations or #CustomerSuccess you know it's often hard to rapidly drill down into + measure the "real impact" of an issue that has just come to light.

Why?

🔺 Data resides in multiple systems to build the complete view

🔺 Real insight is usually a mix of quantitative and qualitative data

🔺 It takes time to build out this analysis

🔺 There are just a few people in the team who have the skills/access

So imagine you're a #CustomerSuccessManager or #RevOpsManager and the impact of (for example) #Finance related issues is suddenly on your mind because you heard a few customers complain about it today... .

.. so what's the question we all want to ask in this situation?

⚠️ HOW BIG IS THIS PROBLEM REALLY 💰💰💰 ?? ⚠️

... and here's one approach we like to help answer that:

In this Demo, Hugh Hopkins demonstrates Delegate (Formerly 42ai) functionality so that Ops, Managers and any front-line operator in the business can INSTANTLY deploy their own customer prioritisation based on whichever factor they like:

🟢 -> Across any GTM systems they want

🟢 -> Through intuitive LLM instructions

🟢 -> Permanently or temporarily

The outcome ?

Piece-of-mind, crystal clear visibility into the breadth of an issue, rapid testing, the data to show your cross-functional partners... and time back in the day for a busy RevOps or CS Manager.

What issues could this help your post-sale team with today?

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Transcript

0:00 One of the ways you delegate 10x as a revenue impact to your team is by helping you understand which customers need attention now, and why.

0:08 That's why we have these components here, that break down what is happening with the customer. In our experience, the frontline has seen it all, and has the best intuition for knowing what should be in these components.

0:19 They also provide excellent foundation signals for machine learning predictions later on. We've now made it possible for anyone with SalesOrg to write these components that actually meet their business needs.

0:31 in a matter of minutes. So, let's jump in and add another example here. Here we have the component creator, and what I can do is simply type a natural language prompt down here.

0:43 In this example, we're wanting to create a component that looks at SLAs being breached in our support tool, so we're going to look at tickets where Invoice, Finance, Bidding and Pay have been done, and we're going to compare that with our revenue impact so that can be data in a different system, perhaps

0:57 our sales CRM. Now because Delegate has a completely understanding of our data structure, it's going to write this code and it's going to do a number of things such as understanding how to tie a Zendesk organisation ID to my Salesforce data.

1:11 It then knows the available information to search, and so it knows that it's got a subject, description, tags, and it's going to do all of that information and then it's going to split out some results here.

1:21 So, let's run a sample and see what that looks like. Running this sample It's actually going to run against real data.

1:29 It's giving me a good idea of what's this would look like if we were to run it at scale. So, let's see some of the results when they come through.

1:38 Okay, uhm, okay, we've got a bug request. It looks alright, it's picking up the information, but I really like those traffic lights, because they enable me to have a very clear understanding of what's happening on the customer.

1:52 So we can just prompt delegate again to add this information and it will then Rewrite the code to then make it that.

2:01 So let's hit Stop there, uhm, and let's Rewrite this here. Okay, so it's then added this information, we've got the common causes here.

2:13 I don't really want that information, let's just take that out. Let's keep the revenue impact, uhm, let's just take that out as well.

2:23 Let's run another, let's clear it actually, and then let's run another sample, and then see what that looks like. Now just to put this in context, before, oh great, so before you'd normally have to work with a BI team to perhaps cram all, to get all of this done, to get this sort of a level of analysis

2:44 , but you always have that stumbling block, that inertia of actually being able to bake it into a frontline workflow, whereas here you can see that in a matter of, I don't know, a minute, I've been able to create a really complex component, I can then hit Push to Production, save this, and then the final

3:03 output is going to look something a little like this. Boom. Three tickets added here. And then that is as simple as it is.

3:13 Like, a matter of minutes to add very complex components that actually meet the requirements of your individual business. Anyway, uh, this is just the start of what we've got to show, we've got some incredible, uhm, features and demos coming up, And yeah, as always, please do get in touch.

3:30 Cheers.

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