Skip to main content

Home/ BI-TAGS/ Group items tagged target

Rss Feed Group items tagged

cezarovidiu

Invata meserie de la Emag - 5 lectii pentru un magazin online care chiar vinde - Conver... - 0 views

  • Lectia 1. Colecteaza adrese de email
  • E suficient sa creezi un magnet de leaduri care sa raspunda unei probleme specifice pe care o au vizitatorii tai.
  • Lectia 2. Foloseste dovada sociala
  • ...11 more annotations...
  • Unul din principiile de influenta ale lui Robert Cialdini este dovada sociala. Acesta spune ca atunci cand ne aflam in fata unei decizii, avem tendita de a-i imita pe ceilalti.
  • recomandari de produse populare: in functie de categoriile de produse pe care le-ai cautat, Emag iti va recomanda si produse similare folosind un titlu care iti arata ca si alte persoane au fost interesate de acele produse.
  • comentarii si feedback: daca arunci un ochi peste produsele disponibile pe Emag, vei vedea ca majoritatea au comentarii, review-uri reale de la cumparatori. Astfel de comentarii vor influenta decizia de cumparare a celor nehotarati.
  • De exemplu, Emag trimite un email catre clienti la cateva zile dupa achizitie.
  • 3. Optimizeaza-ti magazinul online pentru mobil
  • Chiar si Google a observat acest trend, asa ca la inceputul acestui an a atras atentia ca odata cu aparitia noilor algoritmi de indexare, paginile optimizate pentru mobil vor avea doar de castigat.
  • Verifica aici daca magazinul tau online este optimizat pentru mobil.
  • 4. Personalizeaza pagina de eroare 404
  • Pentru a nu pierde un potential client, personalizeaza pagina de eroare 404 adaugand 2 elemente: Un titlu care sa explice ce s-a intamplat (De exemplu, „Pagina cautata nu a fost gasita. Se pare ca ai accesat un link expirat sau gresit.”) Un indemn la actiune (De exemplu, „Click aici sa te intorci la pagina anterioara”)
  • 5. Foloseste efectul amortizorului social Un studiu psihologic realizat in 1972 a demonstrat ca daca stii ca exista cineva cu care poti vorbi, care iti va oferi ajutor in situatiile stresante, aceste momente vor fi mai usor de suportat.
  • Fii pe faza ca sa le raspunzi vizitatorilor la emailuri, la mesajele de pe social media Afiseaza in mod vizibil pe site datele tale de contact Implementeaza un live chat (iti recomand www.purechat.com – e usor de folosit si are si o versiune gratuita)
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
  • ...6 more annotations...
  • 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

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.
  • ...7 more annotations...
  • 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.
  •  
    "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."
cezarovidiu

Using the JDBC Connectivity Layer in Oracle Warehouse Builder - 0 views

  • For example, suppose you want to add support for MySQL. (As of OWB 11g R2, MySQL is not on the list of supported by default platforms.) All you need to do, though, is download the MySQL JDBC driver to put it into the OWB_HOME/owb/lib/ext directory, and add the platform definition for MySQL via a Tcl script that you can run from the OMB Plus console. The contents of such a script is beyond the scope of this article. However, if you want to look at one, check out this post by David Allan, where you’ll find a detailed example of how you can add support for MySQL to Oracle Warehouse Builder 11g Release 2. Also, there is a whitepaper on OTN called the "OWB Platform and Application Adapter Extensibility Cookbook", which goes into more depth than David’s post.
cezarovidiu

Why BI projects fail -- and how to succeed instead | InfoWorld - 0 views

  • A successful initiative starts with a good strategy, and a good strategy starts with identifying the business need.
  • The balanced scorecard is one popular methodology for linking strategy, technology, and performance management. Other methodologies, such as applied information economics, combine statistical analysis, portfolio theory, and decision science in order to help firms calculate the economic value of better information. Whether you use a published methodology or develop your own approach in-house, the important point is to make sure your BI activities are keyed to generating real business value, not merely creating pretty, but useless, dashboards and reports.
  • Next, ask: What data do we wish we had and how would that lead to different decisions? The answers to these questions form top-level requirements for any BI project.
  • ...10 more annotations...
  • Instead a team of data experts, data analysts, and business experts must come together with the right technical expertise. This usually means bringing in outside help, though that help needs to be able to talk to management and talk tech.
  • Nothing makes an IT department more nervous than asking for a feed to a key operational system. Moreover, a lot of BI tools are resource hungry. Your requirements should dictate what, how much, and how often (that is, how “real time” you need it to be) data must be fed into your data warehousing technology.
  • In other words, you need one big feed to serve all instead of hundreds of operational, system-killing little feeds that can’t be controlled easily.
  • You'll probably need more than one tool to suit all of your use cases.
  • You did your homework, identified the use cases, picked a good team, started a data integration project, and chose the right tools.
  • Now comes the hard part: changing your business and your decisions based on the data and the reports. Managers, like other human beings, resist change.
  • oreover, BI projects shouldn't have a fixed beginning and end -- this isn't a sprint to become “data driven.”
  • A process is needed
  • and find new opportunities in the data.
  • Here's the bottom line, in a handy do's-and-don'ts format: Don’t simply run a tool-choice project Do cherry-pick the right team Do integrate the data so that it can be queried performance-wise without bringing down the house Don’t merely pick a tool -- pick the right tools for all your requirements and use cases Do let the data change your decision making and the structure of your organization itself if necessary Do have a process to weed out useless analytics and find new ones
cezarovidiu

Gartner Positions Oracle in Leaders Quadrant for Master Data Management of Product Data... - 0 views

  • For the fourth consecutive year, Gartner, Inc. has named Oracle as a Leader in its “Magic Quadrant for Master Data Management of Product Data Solutions.” (1)
  • “MDM is a technology-enabled discipline in which business and IT staff work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official, shared master data assets. Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise, such as customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts,” according to Gartner.
  • By enabling organizations to consolidate product information from heterogeneous systems, Oracle Product Hub creates a single view of product information that can be leveraged and shared across functional departments in the enterprise, as well as externally with trading partners.
  • ...1 more annotation...
  • "In any product company, accurate product information is a foundation for all major business initiatives, and this requires a robust, comprehensive and flexible product MDM solution,” said Jon Chorley, vice president, supply chain management product strategy, Oracle. "We believe Oracle's position in Gartner's Magic Quadrant for Master Data Management of Product Data Solutions highlights our ability to provide best-in-class functionality across the industry’s most complete MDM portfolio. By using Oracle MDM solutions, companies can obtain a high-quality, common enterprise product record and are better able to support their key business initiatives.”
  •  
    "Gartner Positions Oracle in Leaders Quadrant for Master Data Management of Product Data Solutions"
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.
  • ...2 more annotations...
  • 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

Visual Business Intelligence - Naked Statistics - 0 views

  • You can’t learn data visualization by memorizing a set of rules. You must understand why things work the way they do.
  • you must be able to think statistically
  • This doesn’t mean that you must learn advanced mathematics, nor can you do this work merely by learning how to use software to calculate correlation coefficients and p-values.
  • ...7 more annotations...
  • I am happy to announce that I’ve just found the book that does this better than any other that I’ve seen: Naked Statistics: Stripping the Dread from the Data, by Charles Wheelan (W. W. Norton & Company, 2013).
  • Wheelan teaches public policy and economics at Dartmouth College and is best known for a similar book written several years ago titled Naked Economics.
  • In Naked Statistics, he selects the most important and relevant statistical concepts that everyone should understand, especially those who work with data, and explains them in clear, entertaining, and practical terms.
  • He wrote this book specifically to help people think statistically. He shows how statistics can be used to improve our understanding of the world. He demonstrates that statistical concepts are easy to understand when they’re explained well.
  • If you read this book, you’ll come to understand statistical concepts and methods such as regression analysis and probability as never before.
  • Statistics is more important than ever before because we have more meaningful opportunities to make use of data. Yet the formulas will not tell us which uses of data are appropriate and which are not. Math cannot supplant judgment.
  • “Go forth and use data wisely and well!”
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.
  • ...5 more annotations...
  • 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

ORA-00845: MEMORY_TARGET not supported on this system - Simon Krenger - 0 views

  • size=12g
  • I replaced the “defaults” option with the size=12g option.
  • To make the change persistent, edit your /etc/fstab
cezarovidiu

Octavian Pantis, autorul cartii Musai List, vine la Start-Up Wall-Street. Afla cum sa f... - 0 views

  • Trainerul Octavian Pantis, managing director TMI Training & Consulting. El este autorul cartii "Musai List", un best-seller in domeniu.
cezarovidiu

OBIEE - state of the market - rates | OBIEE Blog - 0 views

  • First observation: Dice. I’m trying to be cautiously optimistic, but it seems as Business Intelligence market in general is picking up.
cezarovidiu

8 Principles That Can Make You an Analytics Rock Star -- TDWI -The Data Warehousing Ins... - 0 views

  • Great design, high-quality code, strong business sponsorship, accurate requirements, good project management, and thorough testing are some of the obvious requirements for successful analytics systems.
  • As a professional in the field, you must be able to do these things well because they form the foundation of a good analytics implementation.
  • Successful analytics professionals should follow a set of guiding principles.
  • ...11 more annotations...
  • Principle #1: Let your passion bloom
  • If you do not love data analytics, it will be hard to become an analytics rock star. No significant accomplishments are achieved without passion. For many people, passion does not come naturally; it must be developed. Cultivate passion by setting goals and achieving them. Realize that the best opportunity in your life is the one in front of you right now. Focus on it, grow it, and develop your passion for it! That excitement will become obvious to those around you.
  • Principle #2: Never stop learning
  • Dig down deeper about the business details of your company. What, exactly, does your company do? What are some of its challenges and opportunities? How would the company benefit from valuable and transformative information you can deliver? Take the time necessary to learn the skills that are valuable for your business and your career. Keep up-to-date with the latest technologies and available analytics tools -- learn and understand their capabilities, functions, and differences.
  • Deepen your knowledge with the tools that you are currently working on by picking new techniques and methodologies that make you a better professional in the field.
  • Principle #3: Improve your presentation skills and become an ambassador for analytics
  • persuasiveness and effectiveness
  • Improve your presentation and speaking skills, even if it is on your own time. Excellent and no-cost presentation training resources are readily available on the internet (for example, at http://www.mindtools.com/page8.html. Practice writing and giving presentations to friends and colleagues that will give you honest feedback. Once you have practiced the basic skills, you need to enhance your skills by improving your
  • You must be able to explain, justify, and "sell" your ideas to colleagues as well as business management. Organizational change does not happen overnight or as a result of one presentation. You need to be persistent and skillful in taking your ideas all the way up the leadership chain.
  • Principle #4: Be the "go-to guy" for tough analytics questions
  • Tough analytics problems typically don't have an obvious answer -- that's why they're tough! Take the initiative by digging deep into those problems without being asked. Throw out all the assumptions made so far and follow logical trial and error methodology. First, develop a thesis about possible contributors to the problem at hand. Second, run the analytics to prove the thesis. Learn from that outcome and start over, if needed, until a significant answer is found. You are now well on your way to rock star status.
cezarovidiu

MicroStrategy Suite | MicroStrategy - 0 views

  • Free reporting software Now enhanced for mobile intelligence Perfect solution for departments Scalable as your needs expand For Windows, Unix, Linux, Solaris, HP-UX, and AIX operating systems and any data source, including Hadoop, SAP BW, Microsoft Analysis Services, Essbase, and IBM TM1.
  • Simple development and maintenance of Mobile apps and dashboards Powerful Visual Data Discovery capabilities Packed with robust analytics Free online support and training Perpetual license to use forever Quick Start Guide brings you from download through your first report
  •  
    "Free Mobile and Business Intelligence Software MicroStrategy's award-winning business intelligence software and mobile app development platform are now available in a convenient free software suite, designed for departments to start building and using mobile apps, dashboards, and reports quickly and easily... and at no charge."
cezarovidiu

Should your company hire a Chief Data Officer? | Enterprise CIO Forum - 0 views

  • Today, every business is a data business. If you’re a manufacturer of consumer goods, supply chain is absolutely central to what you do, and that’s software. It is all about data. That’s the back end. On the front end, social is absolutely critical if you’re in a consumer-facing business. This makes me recollect Geoffrey Moore’s notion about the implications of systems of engagement for corporations. Systems of engagement—such as Facebook, Google, and so on—generate vast amounts of information about consumer behavior. 
  • And this is why enterprises are hiring CDOs. The information in systems of engagement becomes absolutely critical to large-scale successful consumer businesses. If you’re not leveraging it, then your competitor will outpace you in terms of customer knowledge.
  • CDO wears two hats. On one hand, the CDO is responsible for securing the customer data that’s inside the enterprise. In markets where the privacy laws are extremely strict (such as Germany or Canada), that’s a serious responsibility. At a global company, the CDO must manage consumer data at different levels in different countries in different ways, or creating an enterprise standard for data management globally that reflects the toughest regulation anywhere, which is what HP does.
  • ...1 more annotation...
  • The CDO must also deal with this new opportunity to exploit the much larger range of customer information that exists outside the enterprise. The challenge is to link customer information outside the enterprise with the information that’s inside, and do it in such a way that your data doesn’t leak. You want to run your analytics externally—on Facebook’s platform, for example, because it’s impossible to bring all of Facebook’s customer behavior information into your internal systems. So you never want to pass anything out, but you don’t want to bring everything in. It becomes a game of sophisticated integration.
  •  
    "customer knowledge"
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.
  • ...15 more annotations...
  • 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

Magic Quadrant for Advanced Analytics Platforms - 1 views

  • Gartner defines advanced analytics as, "the analysis of all kinds of data using sophisticated quantitative methods (for example, statistics, descriptive and predictive data mining, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover."
  • packaged analytics applications that target specific business domains
  • Revolution Analytics
1 - 20 of 22 Next ›
Showing 20 items per page