Algorithm_2026 R1 - Favorite Things_Ben T

Apr 23, 2026 18:39 · 6:48 · English · Whisper Turbo · 2 speakers

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Lecture Index

0:04

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

I'm Dr. Ben. I help you turn your data into quickly accessible information. And to do that today, I'm going to talk about AI-powered summaries in CRM opportunities and cases. So let's start with a story. So once upon a time, there was a sales manager named Sally. And Sally set out to get the best

0:34

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

information possible around sales opportunities and customer support cases. And there were really three things that Sally wanted. She wanted to take the customer temperature really quickly. She wanted to summarize activities at the click of a button and then get next steps for action as soon as possible.

0:58

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

And so she got her team together and they agreed to get disciplined around data. And they used the Outlook add-in and they brought in emails into the activities on the opportunities so they could have all that data ready. And so they all agreed to it and got some excitement and discipline around it and they were doing it. And then at their first sales quarterly meeting of the year, they got together.

1:27

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

and started going through all the sales opportunities, trying to take the customer temperature, summarize activities, get next steps for action. And it kind of worked, but it was a struggle. And they became a little frustrated because it was difficult to summarize lots and lots of data that they were bringing in. And the team started to lose a little motivation about some of that discipline that they had, bringing in all that data.

1:56

S… Speaker 2 (Algorithm_2026 R1 - Favorite Things_Ben T)

It took too long to work through the information. Action steps would get missed. And so it was a struggle. So the feature set I want to share today helps with that. It's a click of a button. So let me show you what it looks like. Okay, so we're on the Opportunities screen. And you can see just how fast this is. I can click on an Opportunity. And there's a side panel widget here called AI Summary.

2:37

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

And I can click that. And then right now, AI is going to run through this and look through the opportunity, look through all the activities, and then give me those things that I just mentioned in about 10 seconds usually. So I can see that the customer is satisfied. I can see that the latest communication is very positive. They liked our team. They liked our solutions engineer. And then I get next steps about how to close this deal quickly.

3:06

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

Okay, so I can do that just from the opportunities list, but I can also just be right on the screen itself and that same AI summary is here. So this is a different opportunity. Again, it'll run, usually it's typically about 10 seconds or less. And in this summary, I'm expecting to see that it's kind of neutral and that I'm expecting, I'm missing some information. There's not a lot of activity.

3:36

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

I need some next steps are basically get some requirements. This next thing I'll show you is along the same vein with AI, but it's just a bonus feature that's here. I can create the email here and send an email to my contact on this opportunity. I'll just say meeting next week to gather requirements.

4:02

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

And I might even misspell that. I think I spelled that right, but I've misspelled it because I've done this a couple of times. And there's an action up here, similar AI action to refine my reply. So that'll go out and then I'll get an output back here that polishes this email so that I can send that off to Jeff.

4:25

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

So, yeah, I can turn my caveman into a nice email and save me some some time. So that's one thing. So now those are opportunities. Pretty great, huh? So the next thing, if we move on, is let's say you want something kind of specific. No problem. You can just go to the LLM prompt and you can. Here's just the out of box.

4:50

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

But you could tweak this and say, well, I want it to look this way or that way. So you can make it really specific to whatever your business case is around the opportunity. And then I'll shift over to the cases. And you'll see that the functionality I just showed you is here too. So I can click on my AI summary and get it to start.

5:13

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

give me an output of information. It'll give me the same things. So yeah, it's neutral. There's no activity. Now, I know that this is about a credit hold. And so I was able to take some time again here, go do a little research, find the invoice, I could send that to the customer, and then I could tell them that I was able to take this case, I was able to take their account off credit hold, and I can close this case. So again,

5:40

S… Speaker 2 (Algorithm_2026 R1 - Favorite Things_Ben T)

I can go to my activities, create an email, say something like, account is off hold, off credit hold, sorry for delay, and then polish my reply, and then pretty nice, and I can send that off and email that. And then if I'm ready to close the case, I have a similar action button up here where I can just generate my closure notes.

6:22

S… Speaker 1 (Algorithm_2026 R1 - Favorite Things_Ben T)

And there's a tab down here that says closure notes. And you'll see that it'll give me the same kind of output here. What was the problem? What was the description? Symptoms? What was the outcome? So what used to take me all this time to do all this research, fact-finding, data gathering, really has been telescoped into seconds now.

This transcript was generated by AI (automatic speech recognition). May contain errors — verify against the original audio for critical use. AI policy

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