Analytics for Sage CRM webinar

Hello everyone. Happy Wednesday. Thanks for joining us for this webinar. I hope you're not having too much of a cold out there. Here in Northern California we're fairly spoiled. So it's a beautiful day out there in the mid-50s. So let's get started. Before I jump into the presentation per se, let me just give a few words why I started this business back in 2005. I'm a software engineer. I spent many years in my early career actually doing heavy duty programming, Started working with business teams and when I was invited to join the business intelligence analytics industry, I was puzzled initially because reporting was something that I was very comfortable with. I was very technical. But quickly I learned that people who need reporting and data analysis typically don't have the IT skill sets to do the job themselves. So they just have to rely on other people to come up with reports and data analysis. And very often we have to make a decision on a call, on a meeting and we cannot afford to wait someone else to give us information. So the beginning of the vision was, well, I think I can touch this industry and make it better. I can make this whole framework easier, better. And then I decided to blend my skill sets as a programmer as well as a business person to help this industry. So that was, you know, back in 2005 when I started Data Self. It's been, you know, about eight years and I'm excited to talk about the latest and greatest. So let's go for it. Let's go through our analytics for Sage CRM presentation. Let me switch my gears here. So again, my name is Johnny Girardi, I'm Data Sales founder and CEO. Pretty much covered three main topics, why analytics? Then we're going to show a little bit of data self analytics and we're going to open a Q and A session. So first of all, why analytics and where we what packages we work with in the mid market out there? So from a CRM standpoint, we work with Sage CRM with SalesLogix as well as we're already starting to work with Salesforce for 2014. And we can also integrate analytics and data analysis from other ERP systems, you know, from Everest, Microsoft and Sage so far. So when people come to us for CRM, what are they looking for? Well usually CRM is highly involved with sales. So one of the most popular things that people look when they're looking for analytics is having a better understanding or management of opportunities in pipeline. Check the amount of opportunities, the certainty or probability of closing them, who's managing them, who the clients are what is in the cycle and being able to slice and dice this data extensively by regions, by products, if you have products or services. So having a good understanding of the pipeline, of the opportunities, Anywhere, anytime is something that analytics can play a big role for some companies also they have extensive campaign or contact management needs. They have many campaign. Of the initiatives are having better traction. So analytics can play a big role with that kind of management as well. From a support case management standpoint, if you have a support team that is taking calls and want to check time that it's taken to resolve the support calls time, support calls, team effectiveness. Sometimes being able to slice and dice the data and find out that certain people are more effective with some kind of calls and then you can route them appropriately. So being able to have a good understanding of support case is important and analytics can help you understand those initiatives. Sales and CRM goes hand in hand. So just plain looking at or closed sales and understanding how profitable initiatives are, maybe looking from a product standpoint, customer standpoint territory, salespeople trying to find important trends in your sales and pipeline to focus on resources where they matter the most. So having a good understanding of sales and profitability is very critical. Sometimes when you're doing that, you have to combine data that comes from the CRM system as well as from other places such as the ERP or Excel spreadsheets. So analytics can do easy combination of all of this data. So when you're analyzing sales, you have a good understanding of what really matters. Sales commission, CRM and sales is driven by salespeople. And often many of them are paid highly by commissions. Sometimes the commission can be something simple or maybe not. And especially when commission is not simple to calculate, analytics can play a big role. Often we can completely automate the process. Some people spend hours at the end of the month trying to crunch the commission numbers with analytics. Usually this becomes an automated process in real time. Anytime people can check the numbers and see how they're doing their quotas. So analytics clicks can play a big role helping, you know, analyzing sales commission. One of the last most important things as well is when it comes to sales. Sorry. Often people are looking at data coming from different places, again from the CRM system. They may be pulling data from the ERP system and combining both together. Or maybe some of the sales information is coming from Excel spreadsheets. Or if you're selling to big boxes out there like Walmart and Target, maybe these companies, your own clients are giving you some forecast of orders coming through different systems. So the ability to get all of this sales related data into a single place and you can slice and dice the data like it's just a single data source can be critical. And analytics usually plays a big role with that as well. So these are the typical needs that people come to Data Self when they're looking for analytics for CRM and sales. So why Data Self analytics? Well, it goes back to my original vision of when I opened the company, I thought that I could simplify the process and make it better. So we actually are doing, we're simplifying and amplifying analytics. These are the technology components included in our package. We have an ETL SQL Server in Tableau. Now one of the most important things when it comes to analytics is make it easy, make it simple and make it easy for the IT people so they can maintain the system easily without knowing too much programming. And most importantly that the business people, the decision makers, can actually do the job themselves anytime, anywhere. You know, they can be in a call, they can be in a meeting, in a coffee shop, or in front of the client and they should be able to get information as needed. So easy, anywhere so easy is one of the most important components when we are putting our solution together from both IT and business people. Second is, as we said, we amplify our solution. So not only our solution is easy to use for IT and business people, but it comes with a very comprehensive out of the box solution for the two very popular ERP and CRM systems. And if you acquire the whole solution including ERP and CRM today, there's more than 2,000 reports, dashboards and key performance. Because we make it so easy and make it so comprehensive. We say that our solution is like driving a Ferrari. It's a high end, it's fast, it's sophisticated. So we're going to cover the presentation in three different buckets. First of all, I'm going to be talking how people typically access the information in a secured way. Then I'm going to show some simple key performance indicators out of the 2000 list and then I'm going to show some ad hoc analysis how to change things on the fly. So let's do that. So I'm going to switch to the most popular way that people access data, self analytics and typically is through a web server that can be on premises. It can be in the cloud, private cloud, or in our managed services cloud. This interface can be accessed via any kind of the most popular Web browsers, regular PCs, Macs or mobile devices as well as we have apps for Android and iOS for viewing this information. So the idea again is to have anywhere anytime access to the dashboards and the information is highly secured. We use the latest encryption technology that only, only people who have the address to the server, the credentials will be able to access it. Second layer of security is when you log to this portal, it will check your credentials and will give you only the dashboards that you're entitled to. So let's say if you are a salesperson, you'd see the salesperson team dashboard, including let's say CRM dashboards and ERP sales related dashboards. If you're from the finance team, you would see the finance team dash dashboard. If you are an executive, you see the C level Lexi dashboard for instance. So your credentials would allow you to see a set of dashboards based on your credentials. Finally, as you browse through the dashboards, if you select one dashboard, what happens is the system can be set up in a way that will only give you your specific information. So like in this example, I open a sales dashboard and if I'm a salesperson, let's say the California account manager, this dashboard will only show me my California clients, I mean my top California clients this year, today. While let's say Mary, which would be the account manager for Florida, opens exactly the same dashboard, the top customers in Florida, while let's say the big boss looking at the same dashboard would see the top customers across the whole all the territories. So the dashboards can be sensitive to provide each allowed to. All of this is controlled on the server security side. All right, so that's how people access and access it again anywhere, anytime, using Windows, Mac desktops and notebooks, as well as mobile devices such as Android, iOS or any browser or mobile device. Okay, so now that we covered the out of the box, some of the security settings, let's talk about some of the out of the box key performance indicators for CRM folks. So this is one of them. We have many reports and dashboards looking at top performers. When looking at sales in pipeline and CRM information, it's very important to look at the top performers, top customers, top territories, top account managers, top products. If you're selling products or services now, it's also very important to check other kind of trends. And this technology provides many ways to analyze different and important metrics. For instance, usually looking at the top performers is straight and people know who their top customers and top products are. But how about the ones that are growing the most or declining the most in any given time? That's a very critical trend usually the tip of the sales growth curve is usually important. And like this report here is showing the top customers by sales change since last year to date. This could be quarter, quarter to date, period to date, moving window to date, things like that. I see here on the left the sales change this year minus prior year to date. So I can see that these customers are the ones growing the most since last year to date. Most likely happy customers. Salespeople are probably working very closely with these clients. So probably I don't have to do much. It's just humming and going really well. Now how about these customers who are declining the most in sales since last year? If you have recurring customers, Competition is not knocking the door. Something may not be good. So knowing who these customers are declining the most in finding out if something is wrong in a time. But you need to know who they are first. So a report like this looking at top growth and decline again is usually critical. And we have many of reports like this looking across the sales spectrum to give you insights into important initiatives. So this is one example of out of the box key performance indicators that is built in that can be critical. Let me show another one here that can be very important. Exceptional reporting. What is exceptional reporting? Exceptional reporting is when you're analyzing transactions that are no longer happening. So let's say in this example I have recurring customers, regular customers that were buying on an ongoing basis, but they stopped buying. This example I'm looking sales. I had sales in the last 60 days, but no sales in the last 30 days. So why are these customers no longer buying? It's okay, it's seasonal. Maybe they only buy every quarter or so, but maybe not. And again, knowing who they are, people will be able to realize, well, this customer should be buying. Why is not so let me give more close attention to this customer to see what's going on. So looking at recurring, I'm sorry, looking at exception reporting, looking at things that are no longer happening, like what items are no longer selling, what items have been sitting on the on the shelves for too long. Looking at things that are no longer happening can be critical. And our solution has many reports covering those perspectives. Let's take a look at some of the dashboards from an opportunity standpoint. So this one is a very simple way of looking like the pipeline in actual sales. So I'm looking at years that purchase status by account manager. So I have here my account managers and then I have open opportunities in the color of the bars shows the probability from very red Meaning we lost to very green, meaning we won. So here we can see the opportunity status for open opportunities. These are the ones that have been closed. And here we have all opportunities together showing in bubbles and using the same color schema. So very simple dashboard to have a good understanding of opportunities by account manager. Building a dashboard like this from scratch, it takes a few minutes. Actually it takes the time to a donut. Anyway, the donut is an old challenge. We're no longer doing that one. Now we use a Ferrari instead. Anyway, another way to look at CRM information is this a little bit more detailed view. So here we have account manager, the account name or company name products and then by the certainty or probability to close we see how much the opportunity represents. So we can go all the way to the bottom and see the status. And let's say if we want to focus on only one of these type of segments, let's say I don't want to see zero, it's been lost, let's just get out of the way so I can exclude them. I don't want to see sales because it's already done. I just want to see ongoing opportunities. So that's it. Very easily, very quickly. I could be done this on a mobile device, maybe with an iPad for instance. I'm meeting with these people and I want to just focus on certain opportunities. I can just click, choose only certain things, remove certain things and use filters to find exactly the information that you want quickly and easily. Okay, so I'm just going to show you some of the out of the box dashboards. But one of the most important things that we focus on datasoft analytics is giving business people the ability to change things on the fly. Very often when people, decision makers are in calls or in meetings, they need some kind of data information that is not available in a pre configured dashboard or in a pre configured report today. Pretty much if you don't have a solution like data self analytics, you pretty much have to use your gut feeling or call someone else and ask for help. People are busy. So when you ask for help, you may have just got a voicemail and even with the people it may take a long time until this person can give you exactly the perspective you're looking for. This was one of the most important challenges that I took on when I decided to open DataSouth many years ago was my vision was I need to find in the market the easiest to use technology that can enable business people to do the job themselves. Actually the technology, the engine working behind the scenes in Data Self analytics was an engine that was designed by Stanford University professors. These professors, they studied how business people look at data and how they make sense out of it. What kind of data visualization techniques are effective getting insights out of raw business data. These Stanford University professors eventually came up with a technology that has many different facets and the main point is empowering business people with easy access to information. So really. So let's take a look now at one of these dashboards. I'm going to open this opportunity by geography and I'm going to show how extensively I can change a dashboard on the fly. So a dashboard like this, Suppose I were the west coast account manager. Let's say I'm the big boss and I'm meeting with the west coast team and I need to analyze the opportunities in the west coast closely. So suppose that this dashboard was not ready. Well, suppose I'm in this meeting with my iPad, with my west coast team and then I call my assistant and I say, hey assistant, can you please build a dashboard showing geography analysis? I want to see some maps showing bubbles, bigger bubbles for bigger opportunities. Here are the bubbles, bigger bubbles for big opportunities. Slice these bubbles by the certainty of each opportunity. So here is the color schema that is being sliced by. I also want to see. Also what companies or clients are being involved in these opportunities. So suppose I make this call and I ask this person to put together this dashboard because I'm in the meeting. This person, doesn't it person, you know, this person with very little, let's say computer knowledge would be able to build a dashboard from scratch like this in a few minutes, like 5, 10 minutes can do from scratch. Now this person calls me back in a few minutes and tells me hey Johnny, just open this dashboard. So I open the dashboard, I see all the information here. Oh, great job. Let me take it from here. So because I'm the big boss, I have access to the whole set of information, but I'm only looking for west coast team. If I'm using, let's say my iPad, I could come with my fingers and select the west coast areas with my fingers. When I do that now the dashboard changed to reflect who is working with the west coast states and what companies are involved. So right there I see I have these three salespeople working on those half of the west coast of the country. Okay, very well. Well suppose that Lena is my focus. But before I jump into Lina specifically right now, again I'm not looking at past sales or past loss opportunities. I can easily remove those things out of the view. So I'm going to take lost opportunities and won opportunities out of the equation. So right now I have only Lena showing for those states what she's selling. And then I see specifically the customers who are buying and the certified opportunity. Okay, well I'm changing this dashboard extensively here and this does not require much training at all. A business person with little training, sometimes no training, they can do this by themselves. Now I'm a sophisticated business person and actually I want to slice and dice this data further. So for those users who want to go one step further, we can enable this edit button. The edit button, when I click on it like I just did, it gives me full slicing and dicing capabilities to my dashboards. So right now when I clicked it, I have now the three different tabs that were part of the dashboard I was looking at. And now I have here all of these options that can allow me to extensively slice and dice my information. I'm looking at Sage or an opportunity information. And here I see what we call the reporting parameters. And as I'm a business person with very little technical knowledge, I come here and I see business friendly names. So if I go to the. Account manager, company name, industry, my companies, if I go to the, let's say product, if I have product in my CRM, I have product related information. If I go to the opportunity fields, I see opportunity related information. The point is all of these fields, they are business friendly. As a business person, I don't have to learn complicated things. It usually takes a couple of hours, maybe three, four hours for a business person to become familiar with this data panel so they can start slicing dashing things extensively. The other thing is all of these fields, they can have these pop up windows that can have explanation of what the field is so people can write formulas or descriptions of what the fields are. So it's like a self help on the fly. At the bottom we have the measures, the numbers that we're going to look at. So let's make an example here. So I'm looking at this opportunity by company report and suppose I want to slice and dice this more. So let's say I'd like to see this broken down by product. How can I do it? Easy. I go to my dimensions, I find the product and let's say I want to see the product name and if I'm using my iPad, I could drag and drop, let's say into my rows right there I see by company the certainty, product and the opportunity. Maybe I want to change the slides In a different way. Maybe I want to see. I'm a product, product focused person. I can bring the product to the beginning of my query. So by product, by company, then you see the certainty. If I'm the product manager for this product here, I don't care about anything else. I could keep only this one and just analyze it further. Oh, these are the company names. What account managers are associated with this particular company? Well, I can go to my company, find the account manager and I can drag into my before my company, for instance, right there I see by product, by account manager and by company name. The point is it's very easy for a business person with little training to be able to slice and dice the data extensively. They pretty much have to learn how to drag and drop. It is very straightforward. Let me remove some of the components here. Remove the account manager, remove the company name and suppose I want to make some. Actually let me go back to the product name, leave company. Suppose that I want to put some charts here. This show me button. When I click on it, it has these options of charts. This is one of the very cool functionality that the Stanford University professors did. This part of the engine checks the data that you have selected in the query and then highlights what kind of data representations will make sense based on this data. So as a business person, I just have to start, point and click and see what happens until I find a representation that will be informative to my kind of analysis. So data analysis and reporting is like a journey. When business people are trying to figure out something else or something new, they have an idea of where they're going to go. But until they walk the journey, until they view some of this information, they don't know exactly. And that's why when there are two people involved, the business person and a consultant, it takes sometimes many interactions. The business person tells what they want, the consultant goes on, puts something together, comes back, shows, and then, well, actually, can you short this way, can you summarize that way, can you filter it, can you change the colors, can you put a chart? It goes back and forth many times. And again, sometimes people cannot afford that. They have to send information in the middle of the call. And this kind of functionality being helping decision makers walk through the journey easily, quickly, just by point and click is critical. And that's where we focus on user friendliness. As you can tell, there is no mapping capabilities because I didn't select any mapping capabilities. Any geography component. If I go to my company region and now I add, let's say states to My report anyhow. And then I go to my show me button. Now I have geography analysis. So again the tool knows what you're selecting and will help you walk through the journey. All right, so that was. Let me go back here, actually show the last part of the product presentation. Let me go to my sheet here. The last thing is and actually let me take all of the companies. And I want to remove some of the filters, get as much as I want, assume that I come up with this kind of analysis here and I want to focus on this 75% chance of closing in order to work closely with all of these opportunities to be able to close it by the end of the month. And then actually let's say that I'm a savvy Excel user. How can I get information out into Excel? Let's say I can come here in any place. In our front end on the web we have a desktop and even on a mobile device you can click View Data. When you click View data from any standpoint, you can actually have access to the underlying data and you can see all the details associated to it. If you look at CRM information, you can see all related fields from the CRM opportunities or Canyon management, whatever it is. We can also combine when you look at this data, it can be coming data from let's say from your ERP system as well. So anyway, when people download the data or they go to the underlying data, they can see all the transactions and they can even download the information, let's say to an Excel or some other tool that you can further analyze. So in this case I downloaded and I click now in Excel. So I just dumped the whole thing into my Excel let's say now I could go line by line and do like analysis using also Excel as the way to further analyze. Anyway, easy. With a few clicks a business person with little training will be able to slice and dice will be able to access existing dashboards easily anytime, anywhere. They'll be able to filter the dashboards, point and click, export data as well as if they are sophisticated users will be able to click the edit button and extensively slice and dice dashboards. Alrighty. So I hope you enjoyed the test drive with our Ferrari. Let's wrap up with the last part of the presentation. So how about return on investment datacent analytics? Well, one of the interesting things is decision makers. The people who are making decisions decisions to make improvements to the business. If these people are more informed when they're making the decisions, very likely hopefully they'll make better decisions. Usually with Smart people, they'll make better decisions if they are using information. So usually when these people are empowered by a tool like Data self analytics where they can find information anytime, anywhere, by themselves, they'll make better decisions and that will move the needle. So what happens is most of our clients, they get the return on investment in datasoft analytics quickly. How quickly? Well, some examples, for instance, the dashboard that I was showing, showing the top customer by sales growth and decline. Some of our clients, they open the dashboard first thing. They open the dashboard after this installation, they view some of the clients that were declining, that nobody knew what was going on and they were able to find issues, fix them and reverse the trend. So that decision right off the bat was able to save the investment completely in data self analytics. So it can be as quickly as on average, it takes a few weeks or maybe a few months to get the return on investment. But the point is when smart people, smart decision makers make decisions with better information, they make smarter decisions, they move the needle and the investment. Data analytics is paid very quickly. Having said that, how much does Data Self analytics cost? It can change significantly depending on your needs. Also in the pricing model we have purchasing pricing and subscription pricing. So depending on your needs you may be able to get the ball rolling in a four figure investment. Or it can go into five figures depending on pricing model, number of users, modules and so forth. So if you have more information, contact us. We'll be glad to give you an explanation of the options and help you decide if Data Self analyst is a good fit for you. We're offering some very exciting year end incentives. Pretty much we're offering 3% off. But for those who have attended the webinar today, we're giving extra 2%. So if you place the order by the end of the year, you get 5% off licenses. If you are existing client and you're looking for upgrade, we have some very interesting upgrade discounts. That's pretty much about it. So let's open for questions and answers. Because we have so many people in our webinar, we're going to keep you on mute. So sorry about that. But if you use the GoToMeeting panel and you write questions, we'll be able to address your questions and answer them. Let's see here we have some information. Can you send your presentation or audit documentation on this product? Absolutely. Let me tell you this, let me go back here. After this presentation, most likely later today we're going to send you an email that will have a link to our about us events and then at the bottom we have the past events information. So we're going to be able to see the recorded webinar as well as presentation for this webinar. So just wait for that email. By the same token, if you have questions, specific questions, things we have not addressed here, we always love to do one on ones and I can get our sales team involved in discussing your specific needs. We're here to educate it. We're here to educate you, see if it's a good fit if you want to learn about our analytics or if you want to learn about other analytics solutions and which one may be a better fit. We're here to help you make better decisions and move forward even if it comes to choosing another product. Anyway, we want to be a sort of information for all analytics in the market. Other questions so some compliments here. Another question I have here is what kind of data can be integrated between the CRM and the ERP systems? Very good question. Thank you. So Data Self analytics uses a very comprehensive back end system that relies on ultralight data warehousing technology. Even though it's a fancy name. The good news is that means we can combine pretty much any kind of data. We can bring any data from erp, CRM, Excel spreadsheets, point of sale systems, access databases, you name it. As long as this data can be related across these different systems, sometimes using conversion tables, it can be brought in, it can be consolidated. Once that is done on the server side, the good news is people go to analytics and they see a single data set. Let's say I'm looking at my CRM information, it may be blended with ERP information, it may be blended with Excel information, it doesn't matter, it's just data. It's part of my, let's say opportunity analysis. I just slice and dice as a business user. So any kind of data can be integrated, structured that it can be integrated and be helpful for decision makers. Good question. Another question kind of related to the same one, but part of my forecasting data comes from Excel sheets. Can that be integrated too? So this is kind of a classical example of people have forecasting, budgeting, this kind of information in Excel spreadsheets. That information should feed the whole decision making process. So yes, data self analyst can bring that information and let's say show, let's say looking at sales and you have your quotas and maybe you're budgeting and you want to put side by side in analytics. So yes, Excel can be brought in and consolidated just like it was part of the CRRM or the ERP system. Very good. I'm going to take one more question and then we'll wrap it. There's two more questions here. Let me see one that is relevant here. Okay, Looks like we have a question kind of a little sophisticated from probably SalesLogix people. So the question is that how do we compare against typical Spotfire? Actually, typical Spotfire is the built in is one of the built in analytics solutions for SalesLogix. Our solution uses Tableau as one of the engine components. And if you put side by side both we consider Tableau like the Ferrari. The Spotfire is a very good solution as well, but it's more technical driven so it's more designed towards business analysts and IT people, while Tableau is the king of the hill when it comes to user friendliness and ease of use. So if you put both solutions side by side, you'll see that from a business standpoint, tableau is better data analytics. Easier, easier, easier to use, I would say. And when we add the ultralight data warehouse and the over 2000 reports and KPIs that are out of the box in our perspective, we make our solution a lot more valuable as a starting point so it's easier to start getting value out of it already. So I'm going to wrap the session. We have more questions. We're going to be addressing those questions on a one on one basis and contacting those of you who asked questions that were not answered. I really appreciate for your time in this Wednesday. We look forward to talking with you and educating more about analytics and data warehousing. And thank you very much. Have a happy Wednesday and a wonderful holiday season. Thank you folks. Have a great day.