Quick Hits: CRM & Pipeline Reporting for NetSuite and Salesforce

Transcript

Hi everyone. Welcome to today's Quick Hits webinar session on CRM and pipeline reporting for NetSuite and Salesforce. My name is Jim Doyle and I will be going through the presentation today. Just a quick introduction of myself. So I'm a NetSuite admin and ERP consultant. I've been within the NetSuite ecosystem for over five years at this point. I do have a background in supply chain management, logistics, field service management, but I work with clients across all different industries from software to services to product businesses. And really my role here is to understand the business, understand the requirements and help align a technology solution to meet the needs of our prospects and clients.

Today we'll be looking at CRM and pipeline reporting specifically, but just know that we've got reporting outside of just this specific slice of the pie for your other needs when it comes to financial reporting, operational reporting outside of just what we'll see today.

So ZoneReporting was built to solve these challenges that we hear all the time from NetSuite clients. The first is single-level record joins. So natively within NetSuite, and Salesforce for that matter, you're going to find it difficult to connect all the different types of records and transactions that you need to calculate your metrics. So that could be combining marketing and sales data. That could be running key segment analysis by different attributes of your prospect or your items. And then also looking at your pipeline analysis, being able to look at a soft pipeline, something like CRM, which is opportunities, not necessarily committed, along with a more hard pipeline like actual revenue, subscriptions, projects or services that are closed won. Let's combine all that and get one coherent revenue forecast. So we can do a lot in Power BI because we can overcome the single-level record joins.

We can also help knock down those silos of information, get everyone on the same page across all your different departments and systems. Power BI is great for bringing multiple sources of data together and combining them, whether that's project data, CRM data we'll be talking about today. We can look at payroll data, spreadsheet data, pretty much anything. As long as we can get that data into Azure, we can consume it into Power BI and combine it with our NetSuite data, including our CRM data that we'll see today. We also have the ability to build more actionable reports in Power BI. We can use this flexible logic to define our KPIs in very specific ways.

That helps us improve the accuracy of our sales forecasting because we know our business, we know how to forecast, we just need the system to calculate it the way we want it to. And then we can even do something like compare snapshots. So being able to look at historical forecasts compared to current forecasts and see where the deltas are and drill down into that. We can build very actionable reports in Power BI.

We also have time intelligence built out so you can look at your key opportunity metrics year-over-year, month-over-month, you're able to now analyze everything on a trended and comparative basis instead of just looking at current metrics, right? And then manual report building and distribution.

Most NetSuite clients are doing a degree of Excel gymnastics, right? So exporting to Excel, doing manual adjustments, manipulations, calculations, reformatting, Excel gymnastics. We wanna get you out of Excel at least as far as the manual stuff so that you are freed up for value-add activity and actually analyzing the data and making decisions for the business. So let's take a look at, I think this is my last slide. Yep.

So let's take a look at our CRM reporting demo. So I'm logged into Power BI. So you should be able to see my Power BI dashboard here. I'm logged in through the web version of Power BI, but just know that you can also use the desktop version. I've got all my navigations, my Power BI navigations here. I'm logged in with my unique user ID. This is how we define, or we can define very granular permissions and access for your Power BI users. So that when we're looking at the data and the reports, we're controlling what they can access, what they can edit.

This is especially important with sales reporting because you've got reps in there, right? And so you want folks to be able to pull up reports and see just their book of business, just their prospects versus activity that maybe is across the sales team or even in different territories, right? I've got my data model here on the right. These are all those CRM data tables from NetSuite. If you're using NetSuite CRM, can also connect and bring in Salesforce CRM as well as HubSpot actually. So we don't just support NetSuite CRM.

You're going to see all your key record types here. So we've got our opportunities, of course, marketing campaigns, leads, items, sales reps. And then we've got these pre-built measures. And what our measures do are these allow us to actually take that granular data and convert it back into the language of business that we would see on a dashboard. So I can look at, you know, my sales goals, goal versus forecast, goal versus full forecast. Look at it from a won revenue standpoint. All these measures save you a ton of time.

You'll see them in the pre-built reports as we're going through these, but know that you can also build your own reports. I could add a page here and I can drag and drop in and start to build out my own reports using the model. So you do have that option. Now, the pre-built reports that we provide, think of these kind of like templates and you'll see these listed here on the left. So we're going to give these to you in a pretty turnkey way. We can actually get you up and running on these in a matter of weeks as opposed to months. And you can see some of the areas that we're going to be covering.

Looking at opportunity analysis. I mentioned earlier, we can compare snapshots of your forecast and see what's been changing. We can look at cohorts. This is going to group opportunities based on dates that they were piped. So we can see, these are our probabilities. These are our percent of revenue, percent of deals that we can see, based on when opportunities are coming into the pipeline. So you can do some interesting analysis there. Look at our goals, activity versus goals. We can look at our historic deal stages and see how we perform as we continue to move through our funnel. And then we can also look at quotes, right? If we're quoting out of NetSuite, we can do quotes. I don't believe we support that for Salesforce yet, but we can have that conversation as we need to.

Let's look at some of these reports. So starting with our opportunity snapshot. So here we're going to be comparing all of our closed opportunity metrics, which is on the left, to our open opportunities on the right. So I can see I've got 900 ops that we've won. We've got 300 open ops. And then I've got these various metrics for those closed and open ops. And then some visualizations of win-loss.

Here we can see our expected wins by stage. So I can hover over the deal stages for our current open opportunities and see, right, here's the nine deals that are currently in that, what is that, prototype stage. And I can see our probabilities, our weighted revenue based on that probability. So again, able to drill down, zoom in and zoom out on this opportunity data, both our open stuff and our closed stuff.

And then I can also slice and dice this by all those different key attributes, whether it's an attribute of the opportunity itself, like lead source. So here I can come in and filter this by lead source and see, all right, for direct mail marketing, right, we've got 52 opportunities that we've won and we've got 19 open opportunities specifically for that lead source. Or we could look at things from a account attribute. So I could look by industry.

Here we're back to the opportunity, back to the account. There's a ton of ways that you can slice and dice this. And we have this report customizer panel built. So as a rep, I can come in and open this up and say, well, I don't really care too much about the industry. I want to adjust that slicer. And instead of looking at the account industry, I want to go to my product and say, well, let's filter by product category. And now I can close my panel. I've got product category here and we can continue on our way-gaming consoles 55 won, five open. So this page allows you to take a ton of opportunity data, distill it down and dynamically slice and dice it to uncover the insight that you need.

This is a similar view of that data. You'll notice that we are again, parsing closed ops and open opportunities. So it's easy to differentiate between those two, whether you're looking at the closed data, because you want to do some historical analysis to apply to your forward looking forecasting or how you're looking at your open pipeline, or whether you just want to look at the open stuff so that you can action on it now, right? We're done thinking about it, so let's go and win the deals.

This view is going to show us a breakdown by our lead source. And then I can see in blue our won opportunities and then in green we'll have our open opportunities. And now we're starting to pull in things like average deal size by lead source, right? Expected revenue, weighted probability, average deal size of our closed ops. So this is, I would consider this, our average deal size by lead source, our most accurate metric for lead source deal size because we're looking at all of our closed stuff. So you can start to really understand your pipeline, your forecasting, how reps are tracking things on these opportunities as you continue to dig deeper into this. Here we're going to be comparing snapshots of our forecast.

And there's a lot going on on this page. So I'm going to walk through it slowly because I really like this report. So what we're doing here is we are picking a snapshot. And so here I've picked 9 23. And I want to compare that snapshot to the snapshot X days ago. So I want to compare that to our snapshot seven days before that first date. Now you can just set this to your current date.

And then anytime you select that snapshot days, it's just going to backdate it from your current date. So this becomes a really easy way for sales managers to go in and compare their forecasts as they're preparing for those weekly sales calls. So they know what to dig into as far as what changed. Because here at the top, I'm going to be able to see that summary. So I can see for my weekly, monthly, quarterly and annual forecast, what the current forecast is versus the previous forecast as in the forecast in this case from seven days ago.

So this is telling me right away that our annual forecast we've dropped about 13 million. That's a big delta. Well, down in this table, I've got all that opportunity data and I can actually order this. can click on this column and now it's going to sort this column by the change amount. And right away I see, all right, we've got this $13 million delta right here with this account. Let me open that account up and I can see the opportunities that make up that change. And when I look closer, I can see right away that in our previous forecast, we had amounts associated with all these opportunities versus now we do not. So something changed, we don't have amounts. That's why we see the drop.

I can actually drill through to the stage and product details. And this is going to give me more information. So here in our stage history, I can see, all right, here's each of those stages. Any change is going to register as a sort of audit, so to speak. I can see when the modification was. I can see that, all right, it looks like we started to increase probability, increase amounts as we move through April. But then eventually we get to March and I see that we actually kicked all of this out to 2024. So I changed that close date and that's why we are now seeing a change in that annual forecast, but we still have it in the pipeline. It would just be for next year.

So as a sales manager, know, at least now I know that and we can dig into why and, and, you know, again, it talk, it comes back to how you train your reps and how you manage your reps. But at the end of the day, we've all been on sales calls where forecast has changed. What changed? This is your, this is your two minute approach to answering that question.

So really, really powerful tool there. Not a lot of systems can compare snapshots, especially with NetSuite, where you have opportunities changing over time. You're not versioning the opportunity in NetSuite, but what we do here in Power BI is essentially that. So now we can retain and compare historicals, even though the core record has changed over time. This fires me up in case anyone can't tell.

We can also bring in our product details. So here now we're back to our closed and open opp metrics, but now we can see the product here on the left. We can also look at, okay, I mentioned earlier cohort analysis. And you don't really think of cohort analysis when it comes to opportunities and CRM data. But we've seen clients start to use reporting like this to drive action.

What I'm looking at is, a breakdown of all our opportunities. We've got over 2500 opportunities - closed, pending, open, all of them. And I can see a breakdown by the month that they were created. And so we can see, in September of 23, we created 62 deals, 77, 69 down through the months. And so you start to see what we're doing here as we are striating that opportunity number by the month that it was created. I can see the total pipeline by month.

And then what's important to me as a sales manager is I can see our pending revenue. This is the yellow bar and it's depicted in yellow down here too. Why is this important? Because now I can immediately identify these months where we have a ton of pending revenue and the cohort is aging. So we would expect to see a ton of pending revenue here, right? Because these are current active opportunities and it may take us a couple of months to close the deal. What we want to make sure we're staying on top of is these months where we have those aging opportunities with a lot of open pending revenue. And if I click on that yellow, it'll actually filter and show me, right, this is November, 2021.

I can open this month up and see, all right, by deal type, here's all the deals from that cohort. And I can see the pending revenue. So here we've still got a hundred percent of revenue open which is over 10 million. And so I can open up this step and see, all right, and here's all those. I think these would be items on the opportunity or the opportunity itself. I'd have to check on that. You know what? I think it's the opportunity itself, because I'm seeing the deals here. And we can see all that revenue is still pending.

So anyway, as a sales manager, you want to be able to keep these on your radar and whether that's going in and saying, all right, well, what can we do to win that revenue? Or maybe we just need to close it out so that we can, or update something, know, close it, create new one, however we wanna manage that so that we don't have these large chunks of change that are still on the table and maybe throwing off our overall opportunity metrics if we don't think we have a realistic chance of bringing that deal in in the relatively short term.

And then stage probability analysis. So here we can now look at our deal stages. So I've got all my deal stages listed on the left. And then within 30, 60, 90, 180, all the way out to 360 days, I can see the percentage of revenue that we're winning within this day count from when it hits the stage in the funnel. So what does that mean?

Well, let me zoom in on quote. So I click on quote and within 30 days of deals hitting that quote stage, we've won 19% of that revenue this amount. Within 60 days, we're up to 56% of won revenue. Within 90 days, we've won 57%, so marginal increase. And it looks like it stays right around that 60% all the way out to a year. you know, after a year, we've won 65% of the revenue from these quote deals.

Again, why is this important? Because now I can say, well, what are we forecasting? If I click on my quote bar down here, I can see that historically we've won 65% of this revenue. I can see it right there. But the reps are projecting 28% based on the weights that they're applying to the opportunity. So this is telling me that reps aren't as confident in these deals that are hitting the quote stage that our historical probabilities would suggest.

So now I can go in and talk to these reps. I can open up the quote stage. I can see this breakdown by rep and I can see who is close to that 65% because that's going to be consistent with our, again, with our probability histories. If there are reps that are way off, like 10%, I'd maybe want to talk to Andrew or I'd want to talk to 5%, you know, 8%, 63% like this, this is good. We're right on it here with Michael, Michael Jackson. I didn't even notice that, but we're right at that 65%. So that's accurate reporting, again, based on deal stages and based on our historical probabilities. So start to think about the ways you can mentor and train your reps with data like this at your fingertips.

Last thing to mention too is it's all drillable. So you saw me drill through to the stage detail. All these reports, you can really drill into the opportunity detail if you need to. Here last one, we're also comparing our sales goals to our actuals. So we can load in sales goals with something like a spreadsheet, and then you can look at it by territory, by individual rep, by region. We've got some formatting in here, so it greens out or it's red depending on the delta. And now we can, again, do our sales goals versus actual reporting right here in Power BI.

So that brings us to the end of the demo. Hopefully that was a good quick taste of what we can provide. There's a lot more in there. And again, we were just focused on the CRM reporting today, but keep in mind, we can do this for all your reporting. We have a version of this where we bring in 100% of your NetSuite transaction lines. So we actually reconcile to the penny back to NetSuite and can run income statement, balance sheet, top level analysis on your NetSuite data in Power BI. Really exciting.

We get to take advantage of the same flexible reporting that comes with the freedom to define our own joins. If at the end of the day, that's not what freedom is, and I don't know what it is, the ability to define your own joins, we can do that in Power BI.

This is going to be a single platform that folks can access to report across all departments and systems. You saw the CRM component today, but keep in mind, we want everyone in the business, again, with a similar experience logging in to report on their specific area of operation.

And then we want to automate this. So let's take it, let's get these reports automated, let's reduce the manual work that you're doing in Excel and get everything out in front of the users that need them so that they can use them to benefit the business, drive revenue, increase profitability, all that good stuff.

So thanks everyone for your time today. I'll hang out for for questions. If you have any more questions that I don't address now, feel free to go to our website. You can request a demo. Someone will reach out. I'm also on LinkedIn. So feel free to hit me up as well. We can get a demo set up and answer some more of the questions. Thanks everyone.