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cezarovidiu

Successful Social Marketing is So Much More Than Social Media | ClickZ - 0 views

  • In the past, prospects primarily accessed information about a company by interacting directly with a salesperson.
  • As media evolved, mass ads, events, direct mail, and more recently, email, have been the primary tools for engagement.
  • Given the number of consumers posting, blogging, tweeting, liking and sharing, the question for marketers is no longer, Should I use social? It's, How do I use social to its full potential?
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  • Social channels are inherently built for sharing and engagement, making them the perfect place to cultivate valuable business relationships. Integrating social into every marketing campaign you run can move you from a company-to-buyer marketing model to a peer-to-peer influence model. This not only builds trust and brand loyalty, but also positively impacts ROI.
  • It can be tempting to jump right in to all the social media sites out there and start posting away. However, before you publish that first nugget of social marketing content, you need to develop your plan.
  • goals and metrics
  • Build a team that is willing and able to dedicate adequate time to social media endeavors.
  • Many marketers fall into the trap of thinking that social media campaigns can be dealt with on an ad hoc basis, but this couldn't be further from the truth. You don't want your company's online personality to come across as erratic or disjointed, so create a policy that guides those who are participating in the social marketing effort and be sure those guidelines are enforced.
  • Once everyone is on board, encourage them to create engaging content. A good starting place is to ask your team members to answer some of the most frequently asked questions they receive on the various social channels. If everyone is a content creator, you'll never be short of ideas.
  • Word-of-mouth is incredibly powerful and the "share" button on every social media channel allows you to tap into millions of different networks. One of the best ways to interact with your audience is by giving them content they genuinely want to share with their networks. Peer recommendation is extremely valuable because people believe their friends much more readily than a company or marketer.
  • A "Refer-a-Friend" campaign promotes a compelling offer via email marketing and social networks, then grants access to special offers for both the referrers and those referred. Using these campaigns will allow you to gather important metrics, like tracking who the biggest influencers are.
  • A "Social Sweepstakes" campaign allows your entrants to spread the word on your behalf. Through the sweepstakes entry, you gain important user data like who is sharing and where they are sharing most.
  • Finally, a "Flash Deal" campaign is similar to Groupon. Flash deals offer a limited amount of deals for a specific time period through your social platforms. If you use these campaigns, be sure to let participants track the deal's progress! These campaigns are fun and viral ways to spread brand awareness and boost new customer numbers with sharing.
  • make sure your shares are measurable. Monitoring social share numbers is not only an easy way to tell what's working and what's not, but also allows you to see your ROI by showing how far your social reach is in relation to how much time and resources you've put in.
  • Google Alerts and search functions, or enterprise level software like Viral Heat or Radian6.
  • Once you hear what people are saying, you can engage them with relevant responses.
  • Social has evolved into much more than just a channel or tactic and should be an ever-present strategy in all aspects of your marketing. Ultimately, if you come up with a plan, encourage creative content, incorporate social marketing into every stage of your funnel, and measure your results, you'll start to see your social efforts move the ROI needle in the right direction.
cezarovidiu

What's in a Tag? | ClickZ - 0 views

  • The tag-management industry is growing rapidly, as tags are critical to gathering data about your customers.
  • It's the early days for tag management, but the industry is growing rapidly because it's not so much about tags, but about the bigger challenge of using digital data.
  • Where does tag management fit in the data picture? Here's an example someone shared with me recently: He had gone to an antivirus product's website, read the reviews, and bought the software. In the days that followed, however, he suddenly began to see banner ads from that same software maker whenever he visited CNN, ESPN, and other favorite websites. The software maker knew he had visited its website, but not that he already bought the product. They were retargeting him with banner ads at unnecessary cost and no purpose.
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  • Tag management fixes this problem.
  • Most marketing teams struggle with the volume, velocity, and variety of digital data generated every time someone touches the brand. You need insights from the data. You need to understand cross-channel behavior and run predictive "what if" scenarios to improve the effectiveness of your media mix. Tag management can create a foundation to make it easier to use multichannel marketing analytics for these purposes.
  • But one of the big improvements introduced by tag management systems is this: non-technical marketers can do their own tag management.
  • No need to ask IT to deploy tags.
  • You can deploy just one tag, sometimes even just a single line of code, and then manage all the tags through a single user interface.
  • That's a big change from being forced to modify source code on your website.
  • The best tag management systems unite tagged data in one place - automatically.
  • Now the best tag management systems track a data record each time a consumer touches your brand - and deliver it to you in one place.
  • what each consumer has viewed, on what platform, how long they spent with your content, and whether they purchased anything. You get a unified view for everything the consumer has done across all marketing channels.
  • they include the right to be forgotten, easier access to your own data, explicit consent over the use of your data, and privacy by design by default.
  • And, it's clear that the best tag management systems can be a foundation for building those elusive, one-to-one relationships with customers, while using marketing analytics to further improve your marketing decisions about how, when, and where to relate to them.
cezarovidiu

Is Big Data Really Working for Marketers? | ClickZ - 0 views

  • Channel Optimization. Many marketers struggle to optimize each individual channel, let alone optimizing at a customer level across many channels. To the extent that Big Data can help marketers understand what is important in the moment and across touch points, that could be valuable, but it seems more of us need stronger attribution models and analytics methodologies more than access to data. Big Data does seem to be valuable if you want to understand which customers are highest value within each channel and across channels, because the platforms that manage Big Data can handle both structured and unstructured data - which is what you need to truly include Web/clickstream and social data in your analysis.
cezarovidiu

Analyzing Human Data: Take a Dive to Find Out What Your Customers Really Feel - Content... - 0 views

  • What really interests me, and what I think should interest marketers, is what I’ll call signals – one of which is intent. Intent is critical because it can predict action. For example, “Is this person shopping to buy a product like my product?” “Is this person unhappy and needing some form of attention?” “Is this person about to return the product for a reason that is addressable?”
  • Sentiment is one ingredient of intent. If someone is happy, sad, angry … that can be determined via sentiment analysis technologies.
  • Many tools struggle with context.
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  • An example I hear over and over again is “thin” – good when you’re talking about electronics, but bad if you’re talking about hotel walls or the feel of hotel sheets. To do sentiment analysis correctly, you need refinement. You need customization for particular industries and business functions.
  • The market, unfortunately, is polluted with tools that claim to have sentiment abilities, but are too crude to be usable. Even with refinement (e.g., the ability to handle negators and contextual sentiment), approaches that deliver only positive and negative ratings don’t take you very far.
  • There are definitely easy, inexpensive entry points that can meet basic, just-getting-started needs: tools for social listening, survey analysis, customer service (handling contact-center notes, for instance), customer experience (via analysis of online reviews and forums), automated email processing, and other needs. These technologies are user friendly, available on demand, as a service.
  • Text mining:
  • Digital Reasoning, Luminoso and AlchemyAPI.
  • Image recognition and analysis: Image analysis now automatically identifies brand labels in pictures.
  • VisualGraph (now owned by Pinterest), Curalate, Piqora (nee Pinfluencer), and gazeMetrix.
  • Emotional analysis in images, audio, and video: These companies promote analysis of speech and facial expression primarily for structured studies
  • • Affectiva conducts webcam emotional analysis for media and ad research, including development tools to integrate emotional study in mobile apps. • Emotient performs emotional analyses in retail environments, evaluating signage, displays, and customer service. • EmoVu by Eyeris tests the engagement level of both short- and long-form video content. • Beyond Verbal studies emotion based on a person’s voice in real time.
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."
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

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

Choose Your Own Adventure: Map Buyer Personas in a Content Marketing Program | ClickZ - 0 views

  • learn more about the brand or to be entertained or educated in some way.
  • Mapping out the ifs-ands-or-buts pathways for each persona can become complicated, so automation solutions such as Infusionsoft that offer a drag-and-drop interface can make the mapping of the funnel stages manageable.
cezarovidiu

Magic Quadrant for Sales Force Automation - 0 views

  •  
    "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

Magic Quadrant for CRM Lead Management - 0 views

  • Web registration pages and campaigns, direct mail campaigns, email marketing, multichannel campaigns, database marketing and third-party leased lists, social CRM and social networking sites, and tradeshows.
  • SugarCRM
  • Chatter and Data.com
cezarovidiu

Cora Romania implementeaza solutia IBM SPSS - 0 views

  • Cora România a implementat cu succes soluţia completă de analiză predictivă - IBM SPSS Statistics, prin intermediul IBM Innovation Centre şi cu suportul IBM Business Partner.
  • Cora România urmărește creşterea nivelului de satisfacere a clienţilor, fidelizarea acestora şi crearea de oferte personalizate.
  • Soluţia implementată de retailer satisface nevoia de îmbunătăţire a ofertelor de produse pentru clienţii săi.
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  • Soluţia de analiză predictivă va ajuta Cora România să înţeleagă mai bine nevoile clienţilor și schimbările survenite în comportamentul de cumpărare al acestora, astfel încât va putea să dezvolte noi produse şi servicii care să corespundă dorințelor acestora. Totodată, retailer-ul va putea preveni plecarea cumpărătorilor majori, va putea vinde servicii adiţionale clienţilor actuali, va dezvolta produse mai eficiente şi va putea identifica şi minimiza frauda şi riscurile.
  • Soluţia IBM implementată ne va permite să evaluăm corect gradul de informare asupra brandului Cora. În viitor, vom fi capabili să identificăm direcţiile noi de business ce trebuie urmate şi să economisim timp preţios prin automatizarea proceselor de colectare a datelor, concomitent cu creşterea satisfacţiei clienţilor”, a declarat Simona Sahin, responsabil cercetare de marketing Cora România.
  • •Optimizarea tuturor tipurilor de decizii utilizând informațiile cheie obţinute cu ajutorul soluţiilor analitice;•Furnizarea de informaţii care ţin cont de perspectivele şi orizonturile de timp, de la raportarea istorică până la analiza în timp real şi la modelarea predictivă;•Îmbunătăţirea rezultatelor de business şi a managementului riscurilor;Creşterea nivelului de retenţie (menţinere) a clienţilor.
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

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.
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