Good morning, everyone, and welcome everyone. [indiscernible] of TIBCO Spotfire. I'd like to thank you for attending our webcast today, effective sales pipeline management through analytics, presented by Senior Product Marketing Manager, Syed Mahmood.
Just a few items before we begin. If you have questions at any point today, you can submit those using the Q&A module on the bottom right-hand corner of your screen. Syed will field those questions once his presentation and demo have concluded. Also, today's webcast is being recorded so you'll have access to playback through a link, which will be emailed to you after the live session.
So again, thank you for attending today's webcast. And I'd now like to introduce our presenter, Syed Mahmood.
Thank you, Brett [ph]. My name is Syed Mahmood, I'm Senior Product Marketing Manager for Spotfire. And the purpose of today's presentation is to briefly summarize the challenges that sales professionals face and how Spotfire can help address them.
As some of you might know, Spotfire is TIBCO's analytics and data visualization platform. And the plan for today's webcast is to do a brief presentation that shows how sales and pipeline analytics fit into the broader process for customer lifecycle management. And then, I will do a demo of how Spotfire provides those key pieces of insight that sales executives and managers need to be effective in their roles.
So let's get started. So as I mentioned, I would like to start the presentation by first talking about the broader framework for customer lifecycle management because processes related to sales and pipeline management are actually part of this framework. Effectively managing customer lifecycle represents a closed-loop process, this process touches marketing, sales and customer service organizations within an enterprise. And the process of building and maintaining strong relationships with customers starts with a business acquiring a new customer. The relationship is further strengthened when a customer buys additional products or complete solutions from the business. And in the final phase of the customer lifecycle, factors such as customer satisfaction and loyalty play an important role. And this process is fairly challenging because enterprise and businesses need to acquire new customers and build these strong relationships with them while reducing the cost of marketing, selling and servicing to these customers.
As I mentioned in the previous slide, customer relationship management consists of a large number of subprocesses that actually touch different parts of the business. For example, the process of customer acquisition starts with the marketing department planning and conducting a marketing campaign, and the objective of these marketing campaigns is to generate leads. These leads are then tracked and followed up on by the sales department with the objective of qualifying them into opportunities and then eventually converting them into closed deals. So after the relationship is established with the customer, it is now the joint responsibility of marketing, sales and, particularly, customer service departments to strengthen this relationship by addressing customer concerns and improving customer experience, not with the product, and not just with the product but also with the enterprise itself.
So this is actually easier said than done as it requires coordination and integration between various operational, marketing and sales applications and data sources in which customer and sales data is usually dispersed within an enterprise.
So as businesses have invested in CRM systems or sales and marketing automation solutions, analytics have emerged as one of the key components of a successful customer lifecycle management process, and there are several reasons for this. First, CRM solutions or sales and marketing automation systems generate a significant amount of data at every point in the customer lifecycle process. Second, this data is actually, holds the keys to making various CRM processes more effective and efficient, thereby reducing the cost of selling, marketing and servicing to the customers.
What is interesting about this process is that, despite the generation of large amount of data by various marketing and sales automation systems, these systems actually offer fairly basic reporting and analytical capabilities. There is definitely a need for sales and marketing executives and personnel to analyze the data related to their businesses by any dimension that they are interested in. And this is usually not currently offered by a majority of the sales and marketing automation systems available in the market.
So now that we have set the context for sales analytics within the broader framework of customer lifecycle management, let's talk about the challenges faced by executives who are responsible for managing the sales process within an organization. And perhaps, the biggest challenge that sales professionals face with regards to analyzing the efficiency and effectiveness of their sales process is related to various internal and external sources and applications from which sales data actually needs to be extracted and brought together in order to paint a complete picture of the pipeline. And this has important implications: Without integrating the data and extracting them from the various sources, it is quite impossible for a sales executive to get a complete picture of the opportunity or the sales pipeline.
In the earliest slide, I talked about sales force automation or SFA tools such as salesforce.com or Oracle CRM as generating a large amount of data, which is actually critical to making the sales process effective. However, the challenges that these tools themselves offer fairly rudimentary functionality in analyzing this data.
In majority of the cases, SFA tools provide a small number of pre-built reports and dashboard. And if a sales executive or a manager is interested in analyzing the sales metrics that he or she is interested in based on any of the dimensions other than the ones that are actually included in the pre-built report, then he will be severely restricted in doing so.
Another challenge that sales executives face due to lack of effective analytics is the ability to align their sales force with overall corporate and sales strategy and be able to quickly take advantage of promising opportunities and new market segments. Again, if you don't have a complete picture of your sales pipeline, then you won't be able to do so.
Another issue for sales managers and executives is the, is to measure the performance of their sales force and to compare various sales teams and salespersons so that they can take advantage of the knowledge and the skills of the successful sales people in their organization in order to improve the performance of the entire sales force through training and coaching.
And last but not least is the challenge faced by sales executives that actually can have pretty severe financial implications, and that is to inaccurately forecast opportunities and to show them converting into closed deals, which may be based on inaccurate data, which can then lead to missed revenue goals. And that can have, for especially for a public company, that can have pretty severe financial implications.
So now I'll do a short demo to show how Spotfire can be used by sales executives to address some of the challenges that I've just talked about in my previous slide. This, just to set the context for this demo, this demonstration revolves around a fictitious company called Benchmark Capital, which is a provider of business lending and leasing services to companies in a variety of industries, so Benchmark Capital provides business financing to its customers to purchase, lease and distribute capital equipment. And Jim Hansen is the Vice President of Sales at Benchmark Capital. Recently, Jim has been concerned about his sales pipeline. He has heard about deals being lost to competitors from his sales managers. And Benchmark Capital has recently implemented Spotfire for its sales organization so let's see how Spotfire can help some of the questions that Jim has about his sales pipeline.
So I'll switch over to Spotfire now. So this is actually the dashboard that has been designed for Jim. The information in this dashboard is organized in various tabs. As you can see, Jim is currently viewing the pipeline overview tab. And some of the other tabs that are available to him include open deals and campaigns, which we will go into later into the, in the demonstration.
So this, the only graph that Jim sees, provides him with information about how his sales pipeline has been trending over time. And this information has been extracted from salesforce.com, which is Benchmark Capital's sales and marketing automation system. This graph provides him that information about what are, what is the status of various deals in terms of the sales stages that Benchmark Capital uses to track those deals. And these include, for example, for what percentage of opportunities or what is the value of opportunities that have been identified? What is the value of the opportunity for which a proposal has been submitted? What is the value of the deals that have actually been won or lost.
So he can actually see that his sales pipeline has been trending up steadily. Although, for the last 3 quarters, he has been losing -- it seems like he has been losing a higher value of deals to competitors.
So this is a good starting point for Jim. He can, however, also get a view of a similar information by converting it into number of deals. So now the picture changes completely, and now, Jim can see that, although his -- the overall value of his sales pipeline has been increasing, the number of deals have dramatically reduced for the past 3 quarters.
And what does this mean for Jim? It means that, now, his sales force is actually chasing a much smaller number of high-value deals, which means that any deal that Jim now loses or his sales force loses to a competitor, it can potentially have an adverse effect on whether Benchmark Capital's sales organization is going to make their number or not.
So now Jim navigates back to his original screen, and since he is interested in lost deals, he clicks on this link that has been provided to him. So Jim, as soon as Jim clicks on this link, there are various pieces of information that are visible to him. So let's go over these and see, what are they? So as soon as Jim clicks on that link, he can now see the percent or the breakdown of Tier 1 or strategic deals, which tend to be of higher value versus smaller deals. And he can see that a majority of the deals that he, that his organization lost in the third quarter of 2011 are actually larger deals or strategic deals, which is quite disturbing. He can also see the value of the deals as well as the competitors to whom his organization has lost those deals. And here, he can see that Bank of America has been winning deals against his sales team, along with ORIX Corporation and Ford Motor Company. And this is actually, this table provides Jim with information about the details that have been extracted from salesforce.com. And here, he can see information, detailed information about lost deals: account ID, who was the sales manager involved, what was the quarter. Actually, we're looking at all, obviously, since we are interested, in the third quarter of 2011, those are all the deals, what was the deal size and so on and so forth.
And here, Jim is actually looking at an organizational hierarchy in terms of who are the sales managers who lost these deals in this quarter. If he simply slides the slider, he can see that John Flint, who reports to Jim Davis, has lost some deals, as well as Tim Griffin, who reports to David Novak.
So this, so just with a, with one mouse click, he has critical pieces of information about the level of competition that he is facing. So if Jim -- since Jim is interested in Tier 1 deals because those tend to be of higher value, then obviously, he simply goes ahead and clicks on this pie chart to find out what are the Tier 1 deals that he has lost. And immediately, those are highlighted in the various reports that are visible to him so that now he can see that he needs to focus on Bank of America and ORIX Corporation because of the -- those are the competitors that have been taking away strategic or high-value deals away from him. And these are the actually the Tier 1 deals, the details about them that have been lost and, again, a similar kind of information about the sales managers and account executives who have lost these deals. So he was, in a matter of 2 mouse clicks, he was able to find out that maybe at a higher level, what is the level of competition and then drill down into Tier 1 deals which he or she is interested -- which he is interested in.
So another thing that Jim can do is he can click, also click on this link to get another view of similar information. Now he has access to, for example, lost deals that his organization has lost, as well as won in the third quarter of 2011. And this can have important implications. So if he simply, for example, clicks on this, under won deals, he can identify that Bill Tilden is the Account Executive who has won deals against Ford Motor Credit Company. And if there are any opportunities now in which Benchmark Capital is competing against Ford Motor Company, he can either have, he can assign Bill Tilden to that account or he can at least have Bill Tilden give some advice and coaching to the account executive who is in that competitive position against Ford Company in terms of what was the strategies that he used in order to win against that competitor.
He can obviously, based on this information, have a discussion with his sales managers with regards to whether any of these competitors are offering specialized pricing to competitors -- to customers based on which Benchmark Capital is losing these deals. So there, within a matter of one screen and a few mouse clicks, Jim can take some pretty important actions in order to compete more effectively against his competitors.
So -- and also, I would like to point out that this dashboard and all the reports that you see in them are completely interactive so instead of clicking on this link, if Jim would have simply clicked on anywhere on this graph, he would have gotten a similar kind of information, all right? Or he can, for example, simply drag his mouse across these 3 sales stages and get a similar kind of information. Again, this is completely interactive. These links have been provided to him in order to make navigation easier for him, but perhaps more intuitively, he could have clicked anywhere on this dashboard and gotten the information about the current quarter as well as previous quarters if he is interested in those to get, and get that information.
So not only Jim has to worry about the competition that he is facing in the marketplace but he also has to worry about the open, the deals that are open to him in order to -- so that he ensures that he closed those deals in order to make the quarterly sales quota.
And here, Jim can, for example, have a similar dashboard, which provides him with information about the open deals, so deals that have been lost, have been taken away from this view, so he can see what are the deals for which opportunity has been identified, highlighted in pink color, the deals that for which proposal has been submitted and the deals that are in backlog for the 3 quarters -- for the 3 months of the third quarter of 2011. And this table provides him with information about what is the probability of closing those deals.
So let's just assume that Jim is currently, right now, is in July of 2011. So he is interested in forward-looking deals, so the deals that he has a chance of closing in the month of August and September. So if he clicks again on this link, these deals have been highlighted in green color. So you can see that these are the deals that have a probability of closing in August and September, and this is actually whether the probability is of high, low or medium, whether these deals close. What Jim can do is he can select, for example, these 4 deals and identify them that he -- based on his experience, that these are the deals he actually needs to close in order to make his numbers. And now based on that, he can see that these deals are either in the Mountain region. Majority of them happened to be in the Mountain region, about 31% or 32% are in the Western region. And also, these deals happen to be in the finance and capital equipment industries and these are the verticals that Benchmark Capital have identified as the verticals that they compete in.
So again, in addition to competitive information, he has now information about the actual deals that he needs to close. And if he clicks on, for example, this link, he can navigate to the campaigns tab. What this tab is showing him are the various marketing events or programs that have generated the leads for those sales leads. So for example, New York financial, New York CitiFinancial seminar, North American webinar, Internet webcast, which have been highlighted in dark green. When I clicked -- when Jim clicked on the various deals on the previous tab, he can see that these deals and these marketing events were critical in generating the leads in the Mountain region and similarly in the finance and capital equipment verticals.
So what Jim can do is he can actually contact, communicate this information to the Vice President of Marketing and request him to conduct similar kind of programs in order to generate additional leads that have, that can perhaps be closed, followed up in September. And then, his sales force can start following up on them, from October onwards.
So in order to do that, he can actually create a bookmark, and what this bookmark does is it actually captures the navigations that Jim has gone through in order to capture the insight. In other words, for example, if I click on this and then go and, say, apply in -- then his navigation is preserved in this screen. What Jim can do is he can email this link, he can -- into an email to his VP of Marketing. And then when he or she opens his email, she can see exactly the, what Jim means by the marketing programs that he is interested in.
So as you can see that Jim has gone from coming up with competitive strategies to actually working on the deals that he needs to -- his organization needs to close and actually was able to provide information to his, provide some feedback to his marketing -- or VP of Marketing as to what type of marketing campaigns have been useful for him. But let's just see that -- let's just say that Jim is also interested in building some additional reports or dashboards or additional pieces of analysis that he thinks would be useful, what would be the process for doing that? And the assumption that we are making in this demonstration, that Jim doesn't know anything about the data structures that lie under these reports and dashboards and he doesn't have access to any IT person or any person with specialized BI background right now.
So he will simply go and insert a new page, just get rid of these bookmarks and some of these. And then, Jim will go and insert a new visualization. Let's just say that he picks a bar chart. Again, no background in terms of, no information about the data model or the data structures that -- or any information for that matter about the data. So -- and what Spotfire has done is it has taken the first guess in terms of building a bar chart, but this is not what Jim is interested in. Jim would like to actually go ahead and change that. He will do so by clicking on and selecting Time Period for his X axis and his Deal Size for Y axis. And Spotfire is smart enough to realize that this time period is a dimensional hierarchy so he can drag the slider to go from here to quarter to month. And now, he can see his deals for the third quarter.
So now, Jim can go ahead and he can actually do a couple of things. He can click on details-on-demand, and this details-on-demand panel appears, which he can drag down under the chart. So now, whenever Jim clicks on -- I can change the -- whenever Jim clicks on any of these bars, this, the information, the detailed information that lies under that bar in terms -- which have been extracted from salesforce.com is now visible to him. So in business intelligence terminology, this is known as drilling down. And in a lot of BI tools, traditional BI tools, this would actually entail building an entirely new report for which you would need to have information about various fact tables, dimensions, hierarchies things like that, specialized BI concepts and terminology, which Jim has in fact no idea about. But he was able to do that in a matter of mouse, a couple of mouse clicks. Again, this is completely interactive so wherever he clicks on his chart, he is able to see detailed information about the various deals. And he can further customize his chart by removing any of the columns that he is not interested in.
Another thing Jim can do is he can further enhance this report by introducing additional filters that are available to him. So let's just say that he is interested in seeing his pipeline by various regions, which is a fairly common analysis. So he will simply drag his -- the region dimension onto his chart. And now he can go and he would actually like to see it in a stacked bar, and he can here make the chart a little nicer, and now he is able to see his pipeline based on a regional information.
Another thing that Jim can do is he can click, right-click on any of these charts and select, create detailed dimensions. And let's just say that he selects a pie chart. This pie chart will only become visible to Jim when he clicks on his parent chart. So let's just say that he would like to actually see the breakdown of account executives who are working on various sales deals, and here he can select account executives. Now whenever he clicks on the bar chart, the parent chart, he can now see that, for example, in September of 2011, Rebecca Santos is working on 70, approximately 70% of the deals versus Tracy, who's working on 29% of the deals.
And again, this is completely interactive. He only needs to build this once. Similar kind of information, he can add another visualization, and this time, he will select the scatter plot. The look and feel and how the information is presented is completely dynamic. He can simply drag any visualization to any portion of the screen. So here, Jim is actually interested in account names and deal sizes. And here, what Jim can do is he can add another dimension. He would actually like to see these points that are barely visible based on deal size and he can further -- so now Jim can see, again, in September of 2011, what were the accounts, what are their relative sizes, who -- based on this information.
So in a matter of maybe a few minutes, Jim was able to create a fairly compelling dashboard tab, which provides him with information about his sales pipeline based on regional information; the sales, the account executives who are working on these, those deals; detailed information about each of those deals; the relative size of those deals, all very relevant and real-world examples of how a sales executive would manage his or her pipeline.
So now let's go back to the presentation and see that how Spotfire was able to add value for sales executives. And Spotfire, as you can see, enables sales executives to be more effective by accessing and combining data from multiple operational and customer data sources. So in that example, I showed you data being extracted from salesforce.com. But easily, that data could have resided in an Oracle database or an enterprise application like Oracle CRM, or portions of that data could have resided in multiple applications and data sources. And Spotfire would easily extract that data, combine it and present it in a compelling form.
Sales executives will use Spotfire and can be more effective as they have more, clear visibility into all the sales metrics by which they run their business and, more importantly, all the dimensions by which they would like to see their metrics or fact.
So Jim was able to see his pipeline based on value, based on number of deals, based on regions. Also, he was able to build his pipeline reports in a matter of minutes, thereby reducing the time that he spends on administrative task and actually getting engaged with his sales organization in order to close more deals.
Spotfire also enabled Jim to respond to opportunities quickly by making mid-stream corrections. So for example, he was able to see that one of his sales executives was more successful in competing against one of the competitors, and now he's able to perhaps use that salesperson in the deals against that specific competitor. And also, Jim was able to manage the performance of the sales force and improve the accuracy of the sales forecast.
So the reason that Spotfire was able to add all that value is because it has been designed around these principles and those are three-dimensional data exploration. What do I mean by that? It's that Spotfire allows users to freely explore data to any level of detail without requiring IT resources or support or complex or create complex queries, model dimensions, things like that. So Jim had no idea about what are fact tables, dimension tables, and he didn't need to. All he needed to, all he had an idea was about the analysis that he wanted to do, and he was able to do it.
The second design principle or value proposition of Spotfire is user-driven mash-up. So analysts and authors can quickly combine data from disparate sources such as spreadsheets or data warehouses or enterprise applications, and the data from these can be combined into a single analysis, and users are not dependent upon IT support to do so. With Spotfire, analytical applications and predictive models can be blended into a single analysis.
Also, contextual collaboration. We just showed one piece of the various type of collaboration that is possible within Spotfire. But users can -- so Jim was able to, what we call at Spotfire, a moment of "aha." And he can capture that key piece of insight or -- and socialize it and share it within his team and with his peers or even -- and in order to collaborate with them and to get even richer analysis based on the feedback of his teams, peers and colleagues. And because of the contextual collaboration offered by Spotfire, its role-based analysis are, can be shared securely. They're auditable and can be preserved over time.
And one of the more important design principles or value propositions of Spotfire is its role as an enterprise analytics platform, which means that it can be used for to analyze business data, technical data. Spotfire can complement existing BI deployments and leverage corporate data sources. Whether you are a senior executive in an organization or you are a front-line knowledge worker or statistician, the platform provides you with capabilities that allows you to interact with data based on your role.
The Spotfire can scale up and to meet the most demanding enterprise needs ranging from integration, extensibility, security and manageability.
So with that, I will actually finish my presentation. If you would like to learn more about Spotfire, you can visit Spotfire, visit our website at spotfire.tibco.com. There is also a demo gallery available at our website where you can see a large number of demos based on either the various horizontal business processes or specific to industries. And if you would like to get further information, you can email at firstname.lastname@example.org, or you can contact us at one of these phone numbers.
So now we will actually switch over to the questions and see whether we have any questions.
One of the questions that we usually get from customers or prospects is, what are the various data sources from which information can be extracted? So information can be, customer and sales data can be extracted from sources such as Oracle Database, SAP, enterprise applications such as salesforce.com, Oracle E-Business Suite, SAP, ERP, CRM systems. So there is a wide range of systems from which data can be extracted.
So I can see that there aren't any other questions at this time. So I will go ahead and close the webcast.
Okay, actually, so one of the questions that came up is, is it better to use a data warehouse?
Data warehouse can -- so Spotfire would sit on top of data depositories such as a data warehouse, and certainly, that would be one of the use cases where Spotfire would be able to extract information from a data warehouse. But the difference between your traditional BI tools and Spotfire is traditional BI tools assumes that users would be of technical nature: They would have command of concepts like fact tables, dimensions, hierarchies, how the tables are connected, things like that. And if a business user -- in the majority of the cases, business users wouldn't have that information or they would not be well-versed in those concepts. In fact, certain BI tools even require you to write a sequel statement. So definitely, in cases where you are dealing with a large amount of data, that means data needs to be brought into a data -- can be brought into a data warehouse and reconciled and combined together, and then Spotfire can do its magic on top of it.
And so one of the feedback that I have received is perhaps using predictive capabilities of Spotfire in predicting which deals will -- can that be one of the use cases to predict actually which deals will have a higher likelihood of closing based on some kind of algorithm offered. And that is certainly is possible. We can perhaps discuss this in an upcoming webcast.
Does there need to be an explicit relationship between tables? Again, if you are extracting data or certain columns from one table and other columns from another table in order to build a report or a dashboard, those tables need to be connected in order to build that report. That is the most, I guess, likely scenario.
So again, thank you very much for attending the webinar. I greatly appreciate it. Thank you.
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