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cezarovidiu

Magic Quadrant for Sales Force Automation - 0 views

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    "Market Definition/Description Sales force automation (SFA) applications support the automation of sales activities, processes and administrative responsibilities for B2B organizations' sales professionals. Core functionalities include account, contact and opportunity management. Additional add-on capabilities focus on improving the sales effectiveness of salespeople, such as sales configuration, guided selling, proposal generation and content management, and sales performance management support, including incentive compensation, quota, sales coaching and territory management."
cezarovidiu

Difference between CRM lead and an opportunity - Pipeliner CRM Blog - 0 views

  • Any individual fish or pod of fish in your sea represents one lead.
  • Your Nemo will not be the first or the second fish that you catch. At the beginning, you will have very little information about the Nemo you would like to catch. You will start to examine your fish and create some criteria as to how Nemo should look like. In other words, you are qualifying your fish.
  • Lead = Any Fish in The Sea. Opportunity = Nemo
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  • The process of examination and adding the criteria represents your sales pipeline strategy. It’s always true that: “Without a commitment to pursue working together (something that results in this company potentially buying from you) there is no opportunity.” - Anthony Iannarino
  • At the end of your examination ie. of your sales process, you will either let the fish swim back into your sea (lost opportunity) or you will put Nemo into your aquarium (won opportunity). Won Opportunity = You have found Nemo Lost Opportunity = You have not found Nemo
  • A Lead – is a contact or an account with very little information. It could be just a person who you might have met at a conference. You will need to retrieve more information regarding this lead in order to create (qualify) an opportunity in your sales pipeline.
  • A old sales rule says: “If you have never contacted your contact, it’s a lead.”
  • An Opportunity - is a contact or an account which has been qualified. This person has entered into your buying cycle and is committed to working with you. You have already contacted, called or met him and know their needs or requirements. The old sales rule says: “The opportunity is a deal that you have the possibility to close!”
  • “Think about the difference between a lead and an opportunity as an evolving process i.e. each lead needs to be qualified to an opportunity. There will always be plenty of leads in your sales territory, but only few of them will qualify to become real sales opportunity.”
cezarovidiu

Filling a Critical Role in Business Today: The Data Translator - Microsoft Business Int... - 0 views

  • a lot of articles calling data scientists and statisticians the jobs of the future
  • there are more immediate needs that, when addressed, will have a much greater business impact.
  • Right now we have huge opportunities to make the data more accessible, more “joinable” and more consumable. Leaders don’t want more data – they want more information they can use to run their businesses.
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  • Every company has hundreds of millions of records about their sales, expenses, employees and so on, with dozens of insights yet to be discovered through simple comparison or triangulation of relevant data.
  • Why don’t we focus on this? I think because it’s very difficult to do – being successful in this “data translator” role requires a unique set of skills and knowledge, the combination of which I call the BASE skillset: Business understanding Ability to synthetize and simplify Storytelling skills Expertise in data visualization
  • Business Understanding This one seems obvious, but it doesn’t mean simply understanding the financials of a business. Rather, it means truly knowing the operational details, the incentives, the install base, market growth, penetration, the competition, etc. An analyst can’t just know the technical aspect of a report or the math behind the numbers, but what is truly driving a pattern in terms of product quality, competition, incentives and/or offerings. The best analysts are able to mathematically isolate the key levers of a trend and then suggest actions to react to or take advantage of those trends. Ability to Synthetize and Simplify This is, in my opinion, the most underrated and underappreciated skill. Combing through thousands of data points and netting out 3-4 key issues in under 10 minutes, and then communicating these to a group of execs with very different analytical skills, is truly difficult. The key is to make it simple but not simplistic, which means you still capture the complexity even as you get to the few core insights. It requires a very thorough effort to gather all the relevant information before categorizing, prioritizing and deciding if it is significant. After a while, you become an expert and can sniff things out quickly. At the same time, there is the danger of missing anomalies when you jump to conclusions based only on a summary look.
  • Storytelling Skills There are stages that should be followed when explaining complex ideas, something data translators are frequently expected to do. The best storytellers start by giving context and trying to couple the current discussion to something the audience already knows, ensuring the story is well structured and connected. We have to move from a “buffet style” business review with thousands of numbers packed in tables to a layered approach that will guide the audience to focus first on the most relevant messages, diving deeper only when necessary. Minto Pyramid Principles, which are built around a process for organizing thought and communication, are helpful in making sure you really focus on what is important and relevant, versus being obsessed in telling every fact. Expertise in Data Visualization I am glad to finally see so much focus on Information Visualization and I believe this is correlated to the explosion of data. Traditional methods of organizing data do not facilitate an intuitive understanding of key information points or trends. For instance, the two examples below contain data on car sales across the U.S. The first, an alphabetized list, is much less intuitive than the second, which shows those sales on a map in Power View. With Power View, right away you can identify the states with the highest sales: CA, FL, TX, NY. (Workbook available here)
  • There is no better way to see patterns or trends than data visualization, making expertise in this area – both technical and analytical – critical for data translators.
cezarovidiu

Using Email to Get the Conversion (Without Stalking) | ClickZ - 0 views

  • The reality of the inbox is that people subscribe to a lot more stuff than they are committed to reading. As a result, they sift through the advertising and marketing noise to find the gems--the messages they connect with and that add value to their lives.
  • your email has to add value to your customers' lives
  • From your initial sign up process to the content and frequency of your messaging, your most important job is showing your audience that you respect the privilege of being invited into their inbox.
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  • Rule #1: Don't ask for more information than you'd personally be willing to give. Asking for too much information in an opt-in form can be a major deterrent to visitors who would otherwise be likely to sign up.
  • Make signing up as simple as possible by requiring only the bare minimum. In many cases, this means just the email address. Every field you add to your form beyond that will decrease the chances of someone filling it out.
  • Here's another tip: If you really want to convince a visitor to opt in to your communications, make it clear that the value they'll receive greatly outweighs the hassle of signing up
  • An opt-in form that says something like "Sign up for our newsletter," doesn't offer any benefit to the visitor. Give people a reason to opt-in by offering them something they'll care about, like: "Sign up for our monthly newsletter and gain instant access to our 57-page e-book on X."
  • Offers of buying guides, e-books, case studies, online videos, and instant coupons are all great incentives to test.
  • I recently welcomed two kittens into the family and we buy our supplies from Petco. As soon as I signed up for Petco's Pals Rewards program, the store proceeded to email me every single day with a new coupon offer. Can you guess what I did? Yep, I opted out. I'll still buy pet supplies from Petco, but at some point, the annoyance became greater than the value of the coupons.
  • One of the most critical steps in structuring your e-commerce email campaign is to set the publish frequency to align with the types of products you're selling and who you're selling to. At a bare minimum, segment your audience into two broad categories of current customers and prospects.
  • When you're communicating with prospective customers, offer discounts, promotions and pre-sale notifications and buying tips in your emails, to move them along the conversion path.
  • You can further segment your email list by those you send to frequently, those you send to less frequently and those you send to only sometimes.
  • You'll find your sweet spot by tracking conversions from the list, looking at the opt-out rate and by allowing your audience to manage the frequency of the communications (for example, by giving them the option to change the frequency before they opt out entirely).
  • When most people opt in to receive B2B email communications, they are at the top of the conversion funnel; the "awareness" stage. A smart B2B email campaign will then provide the right content to bring the buyer deeper into the conversion funnel, with content specific for each stage of the buying cycle.
  • Here are some ideas to get you started: Explore learning concepts that get the reader up to speed on the ideas surrounding your services, and that demonstrate your brand's unique perspective.  Dive into the ideas behind why a service like yours is so important to customers, what to look for in a company, and how your service or ideas compare to others.  Answer common questions your prospective customers have at each stage of the buying cycle and even after the purchase.
  • Don't forget you're not selling to rational people. Most of the buying decisions in a B2B environment are based on what could happen if the choice is wrong. Unlike the consumer market, where an item can be easily returned if it doesn't meet the buyer's needs, making the wrong purchase decision in the B2B arena could be extremely costly.
  • Your goal as the marketer is to arm the potential buyer with content that will reduce any fear and uncertainty about selecting your business over the competition.
  • Think of topics like, "7 Biggest Mistakes People Make When Choosing [insert your service here]" as a basis for building your case. If you have a sales team, ask them for the most common objections they hear from prospects, and create your content around the specific concerns known to be top-of-mind for many buyers.
cezarovidiu

BI Brief - Four Legs of a Successful Business Intelligence (BI) Project Team - 0 views

  • 1. Project Sponsorship and Governance 2. Project Management 3. Development Team (Core Team) 4. Extended Project Team
  • 1. Project Sponsorship and Governance IT and the business should form a BI steering committee to sponsor and govern design, development, deployment, and ongoing support. It needs both the CIO and a business executive, such as CFO, COO, or a senior VP of marketing/sales to commit budget, time, and resources. The business sponsor needs the project to succeed. The CIO is committed to what is being built and how.
  • 2. Project Management Project management includes managing daily tasks, reporting status, and communicating to the extended project team, steering committee, and affected business users. The project management team needs extensive business knowledge, BI expertise, DW architecture background, and people management, project management, and communications skills. The project management team includes three functions or members: Project development manager - Responsible for deliverables, managing team resources, monitoring tasks, reporting status, and communications. Requires a hands-on IT manager with a background in iterative development. Must understand the changes caused by this approach and the impact on the business, project resources, schedule and the trade-offs. Business advisor - Works within the sponsoring business organization. Responsible for the deliverables of the business resources on the project's extended team. Serves as the business advocate on the project team and the project advocate within the business community. Often, the business advocate is a project co-manager who defers to the IT project manager the daily IT tasks but oversees the budget and business deliverables. BI/DW project advisor - Has enough expertise with architectures and technologies to guides the project team on their use. Ensures that architecture, data models, databases, ETL code, and BI tools are all being used effectively and conform to best practices and standards.
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  • 3. Development Team (Core Team) The core project team is divided into four sub-teams: Business requirements - This sub-team may have business people who understand IT systems, or IT people who understand the business. In either case, the team represents the business and their interests. They are responsible for gathering and prioritizing business needs; translating them into IT systems requirements; interacting with the business on the data quality and completeness; and ensuring the business provides feedback on how well the solutions generated meet their needs. BI architecture - Develops the overall BI architecture, selects the appropriate technology, creates the data models, maps the overall data workflow from source systems to BI analytics, and oversees the ETL and BI development teams from a technical perspective. ETL development - Receives the business and data requirements, as well as the target data models to be used by BI analytics. Develops the ETL code needed to gather data from the appropriate source systems into the BI databases. Often, a system analyst who is a expert in the source systems such as SAP is part of the team to provide knowledge of the data sources, customizations, and data quality. BI development - Create the reports or analytics that the business users will interact with to do their jobs. This is often a very iterative process and requires much interaction with the business users.
  • 4. Extended Project Team There are several functions required by the project team that are often accomplished through an "extended" team: Players - A group of business users are signed up to "play with" or test the BI analytics and reports as they are developed to provide feedback to the core development team. This is a virtual team that gets together at specific periods of the project but they are committed to this role during those periods. Testers - A group of resources are gathered, similarly to the virtual team above, to perform more extensive QA testing of the BI analytics, ETL processes, and overall systems testing. You may have project members test other members' work, such as the ETL team test the BI analytics and visa versa. Operators - IT operations is often separated from the development team but it is critical that they are involved from the beginning of the project to ensure that the systems are developed and deployed within your company's infrastructure. Key functions are database administration, systems administration, and networks. In addition, this extended team may also include help desk and training resources if they are usually provided outside of development.
cezarovidiu

10 Reasons Why CEOs Don't Understand Their Customers - Forbes - 0 views

  • 1) Do bad customer experiences cause people to switch brands? In a 2011 research project conducted by CX application vendor RightNow, 89% of consumers said that yes, a bad experience has spurred them to switch brands. But in the brand-new study of business-executive perceptions that’s the subject of this column, only 49% of the surveyed executives said yes.  QUESTION: What steps do you need to take to close this dangerous perception gap? 2) While 97% of executives say CX is critical to the success of their company, and 91% say they’re committed to making their company a CX leader, only 20% would rate their own CX initiatives as “advanced,” with a dedicated CX leader in place, initial projects pushed to the optimization phase, and the overall project extended to new channels and groups . QUESTION: What are the obstacles preventing you from aligning your actions with your words? If you say it’s a “budget” issue, aren’t you really talking about strategic priorities rather than line items? 3) Most companies have a clear and direct understanding of the looming CX challenge and the powerful interaction of social media. The study found that the top two drivers for CX initiatives are (a) rising expectations from customers (59%),  and (b) the impact of social media on customers’ ability to broadcast good and bad experiences (37%). Now, even if you’re able to somehow rationalize those findings, here’s one that not even the most-accommodating executive can dismiss:
  • 4) Being a CX laggard can cost those companies many tens of millions or even hundreds of millions of dollars in lost revenue: executives estimated that the lack of positive, consistent, and brand-relevant customer experience can cause them to lose out on a staggering 20% in annual revenue.
  • Worse yet, all that money’s likely to wind up in the pockets of your competitors!
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  • 5) While 81% of execs said they believe that social media is an essential ingredient in delivering great customer experiences, 35% of responding companies still do not have social media for sales channels, and another 35% still do not have social media for customer service. QUESTION: How do you plan to close that dangerous gap?
cezarovidiu

Gartner's 2012 Magic Quadrant: Do Business Intelligence Vendors Lack Vision? - Enterpri... - 0 views

  • Pentaho, for instance, is one of this year’s rookies. It had been knocking on the door for a year or two and received an honorable mention last year. It needed to increase its overall sales figures to be cited by Gartner, a requirement it satisfied this year.
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    "While Leaders and Niche Players abound in Gartner's 2012 Magic Quadrant for Business Intelligence, only two companies placed in the Challenger category and Gartner didn't name any vendors as Visionaries. What gives?"
cezarovidiu

Magic Quadrant for Business Intelligence and Analytics Platforms - 0 views

  • Integration BI infrastructure: All tools in the platform use the same security, metadata, administration, portal integration, object model and query engine, and should share the same look and feel. Metadata management: Tools should leverage the same metadata, and the tools should provide a robust way to search, capture, store, reuse and publish metadata objects, such as dimensions, hierarchies, measures, performance metrics and report layout objects. Development tools: The platform should provide a set of programmatic and visual tools, coupled with a software developer's kit for creating analytic applications, integrating them into a business process, and/or embedding them in another application. Collaboration: Enables users to share and discuss information and analytic content, and/or to manage hierarchies and metrics via discussion threads, chat and annotations.
  • Information Delivery Reporting: Provides the ability to create formatted and interactive reports, with or without parameters, with highly scalable distribution and scheduling capabilities. Dashboards: Includes the ability to publish Web-based or mobile reports with intuitive interactive displays that indicate the state of a performance metric compared with a goal or target value. Increasingly, dashboards are used to disseminate real-time data from operational applications, or in conjunction with a complex-event processing engine. Ad hoc query: Enables users to ask their own questions of the data, without relying on IT to create a report. In particular, the tools must have a robust semantic layer to enable users to navigate available data sources. Microsoft Office integration: Sometimes, Microsoft Office (particularly Excel) acts as the reporting or analytics client. In these cases, it is vital that the tool provides integration with Microsoft Office, including support for document and presentation formats, formulas, data "refreshes" and pivot tables. Advanced integration includes cell locking and write-back. Search-based BI: Applies a search index to structured and unstructured data sources and maps them into a classification structure of dimensions and measures that users can easily navigate and explore using a search interface. Mobile BI: Enables organizations to deliver analytic content to mobile devices in a publishing and/or interactive mode, and takes advantage of the mobile client's location awareness.
  • Analysis Online analytical processing (OLAP): Enables users to analyze data with fast query and calculation performance, enabling a style of analysis known as "slicing and dicing." Users are able to navigate multidimensional drill paths. They also have the ability to write back values to a proprietary database for planning and "what if" modeling purposes. This capability could span a variety of data architectures (such as relational or multidimensional) and storage architectures (such as disk-based or in-memory). Interactive visualization: Gives users the ability to display numerous aspects of the data more efficiently by using interactive pictures and charts, instead of rows and columns. Predictive modeling and data mining: Enables organizations to classify categorical variables, and to estimate continuous variables using mathematical algorithms. Scorecards: These take the metrics displayed in a dashboard a step further by applying them to a strategy map that aligns key performance indicators (KPIs) with a strategic objective. Prescriptive modeling, simulation and optimization: Supports decision making by enabling organizations to select the correct value of a variable based on a set of constraints for deterministic processes, and by modeling outcomes for stochastic processes.
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  • These capabilities enable organizations to build precise systems of classification and measurement to support decision making and improve performance. BI and analytic platforms enable companies to measure and improve the metrics that matter most to their businesses, such as sales, profits, costs, quality defects, safety incidents, customer satisfaction, on-time delivery and so on. BI and analytic platforms also enable organizations to classify the dimensions of their businesses — such as their customers, products and employees — with more granular precision. With these capabilities, marketers can better understand which customers are most likely to churn. HR managers can better understand which attributes to look for when recruiting top performers. Supply chain managers can better understand which inventory allocation levels will keep costs low without increasing out-of-stock incidents.
  • descriptive, diagnostic, predictive and prescriptive analytics
  • "descriptive"
  • diagnostic
  • data discovery vendors — such as QlikTech, Salient Management Company, Tableau Software and Tibco Spotfire — received more positive feedback than vendors offering OLAP cube and semantic-layer-based architectures.
  • Microsoft Excel users are often disaffected business BI users who are unable to conduct the analysis they want using enterprise, IT-centric tools. Since these users are the typical target users of data discovery tool vendors, Microsoft's aggressive plans to enhance Excel will likely pose an additional competitive threat beyond the mainstreaming and integration of data discovery features as part of the other leading, IT-centric enterprise platforms.
  • Building on the in-memory capabilities of PowerPivot in SQL Server 2012, Microsoft introduced a fully in-memory version of Microsoft Analysis Services cubes, based on the same data structure as PowerPivot, to address the needs of organizations that are turning to newer in-memory OLAP architectures over traditional, multidimensional OLAP architectures to support dynamic and interactive analysis of large datasets. Above-average performance ratings suggest that customers are happy with the in-memory improvements in SQL Server 2012 compared with SQL Server 2008 R2, which ranks below the survey average.
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    "Gartner defines the business intelligence (BI) and analytics platform market as a software platform that delivers 15 capabilities across three categories: integration, information delivery and analysis."
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