Excited Me: Cool! The latest thing! A vast untapped resource of dialog and opinion straight from customers!

Wary Me: This stuff is mostly free-form! How are we ever going to glean relevant, actionable data from these sources? It’s like the Wild West out there…

Some basic social metrics are easy to gather and interpret. How many Facebook likes did we add this month? How many unlikes? How many Tweets were made with a hashtag we might expect, like #ProductName? How many people liked our client’s latest Facebook post? It’s a good start, but our client’s management wanted more in-depth insight.

There are several tools available for social media analytics. Visible Intelligence, Radian6, Sysomos (MAP and Heartbeat), Nielsen’s BuzzMetrics, Crimson Hexagon, etc. They all offer valuable insight but go about it in very different ways. Instead of picking a tool and prying out what we could, we worked backward from our client’s requirements. We tried various tools, analyzed the results, and chose the solutions that provided the most relevant analyses for their needs. Here’s a partial list of some of the in-depth analyses we were able to generate:

Buzz Volume: Using keyword searches across Facebook, Twitter, and select blog, video, and photo sites, we came up with a “buzz” volume that we could track over time. This is good to watch for overall social interest—for example, to see the buzz from rolling out a redesigned website or a new product version.

Sentiment: Some tools are quite good at classifying posts by sentiment: positive, negative, or neutral. Tracking counts of posts by sentiment month-to-month proved to be very useful, particularly around new product version releases and press releases. For further insight we picked out specific sample posts, positive and negative, and provided links to the actual posts.

Topics by Media Type: This breaks out a percent of posts by where they occurred: Facebook, Twitter, blogs, etc. Watching shifts in these volumes proved valuable. For example, we knew that discussions in this client’s forums tended to be mostly about troubleshooting technical issues, so an increase in forum buzz proportionally to other sources could indicate an emerging technical issue.

Top Contributors: We identified the URLs of forums, URLs of blogs, and handles of Twitter accounts providing the highest number of posts in the month. This provides a nice short list for further investigation of who is “buzzing” about our client’s product the most and might be worth approaching for a more formal relationship. For example, a person who frequently blogs about usability of the product might be an excellent person to have as a beta tester.

Competitive Analysis: Why just track buzz volume for the client’s product? We track buzz volume for competitors’ products as well, then combine and track over time to see how our client stacks up. The percentage that our client’s buzz contributes to the overall buzz in their category could be termed “Share of Voice” and is a good metric to track. When our client releases a new version, does their Share of Voice go up? If not, do they need to retool their launch marketing efforts?

Website Visits by Referring Domain: Most common web traffic tracking tools can report the domain from which a visitor came. Because many of our client’s social media posts include a call-to-action to click on a link to our website, we can track referrals from twitter.com, linkedin.com, etc. to determine how much web traffic is being driven by their social campaigns.

Success Events by Referring Domain: Going one layer further with web analytics, we worked with our client to define specific “success events” we wanted to track. These were desirable actions taken once the visitor landed on the client’s website, such as watching a video, reading a whitepaper, or downloading a software trial. Analyzing these success events by referring domain allowed us to see the level of engagement of visitors from social sites. Combining Visits and Success Events, both by Referring Domain, we calculated a “Success per 100 Visits” metric-another good way to see how effective our client’s social media posts are at engaging customers.

Blog Traffic Analysis: We used standard web analysis tools to track interaction on our client’s blog. Initially, their blog showed entire articles on the main page. To enable more detailed analysis, we drove changes to their site structure so that the home page shows only the first several lines of each article with a “Read more” link. This way, each full article receives a unique URL, and we’re able to track how many in-depth reads each article is receiving.

Blog Traffic by Referring Domain: Again, it’s interesting to see how people are getting to our client’s blog. This analysis reveals some noteworthy sources of links to their blog articles, and it can also identify sites that could be approached for a more formal relationship.

In its infancy, the process of analyzing social media data can yield some very helpful insights for marketers and managers. It’ll be exciting to see how the tools evolve—no doubt providing richer and more accurate data in the future—and to discover how we can further leverage this rich source of customer feedback data to benefit our clients.

This week it was hard to choose just one favorite—we’ve seen pictures of the Inc. Leadership Conference, an adorable baby, and the art near our lovely downtown neighborhood.

But Eric’s picture from Portland was irresistible, because we’re very excited about our new partnership with Webtrends (which is based in Portland). You can now find us on their partner page, and we can’t wait to see how their analytics tools enrich our ability to help clients with customer intelligence. (Not to mention giving us an excuse to visit Portland more often!)

Point 1: People, Process, and Technology:

“The Projectline approach has three core dimensions, which revolve around people, processes, and tools. While many consulting firms focus primarily on tools and processes, Projectline believes the role of people is just as important because they possess the institution’s collective knowledge and are responsible for implementing information tools and processes. These core dimensions are Data Stewardship, Data Governance, and Technology. All of them must be taken into account as an organization undertakes a project to discover its master data and to design, build, and implement a solution.”

As in healthcare, new marketing measurement initiatives often focus on process or tools, but underplay the vital role of people in getting good data that leads to valuable insights. Without full participation from marketers, the data going into the system will always be flawed—and the stories the data tells will always be untrustworthy. People need to trust the technology and understand the process. In turn, the technology needs to be created in a way that honors existing processes. And the processes need to be developed with a full understanding of the technology and how it fits into people’s work.

Point 2: Quick Wins:

“Develop effective implementation plans for ‘quick wins.’ Quick wins are particularly important because they lead functional areas to recognize the importance of MDM and accept it right away.”

When you create a long-term system to optimize marketing by measuring marketing initiatives, it can be easy to get focused on crafting a pure system or shifting ingrained behaviors and taxonomies. But to gain the confidence of teams—and executives—it is vital to define early success and make it achievable. It will be much easier to justify continued investment in a program if you can point to success within the first quarter after implementation, rather than pointing to numbers far into the future.

But it’s not all we do. We also have a Business Intelligence (BI) team, and they feel as passionate about BI as the customer evidence team does about case studies, good content, and social media. To share some of their expertise and wisdom, we’ve just published an article about Master Data Management (MDM) for the healthcare industry, and we’re thrilled to share it with you. Here’s a brief overview:

Market and regulatory issues in the healthcare industry are driving and increasing the need for accurate and efficient flow of information, with the result that healthcare providers must ensure that their data is relevant, up-to-date, and comprehensive. We see Master Data Management, an approach to creating and maintaining consistent data, as a key IT strategy for achieving this goal.

Our article looks at how you can use Master Data Management as a key strategy for addressing these challenges and discusses the Projectline Services approach to MDM for healthcare. We apply three core dimensions—processes, tools, and especially people—to maximize “data wellness” and help make healthcare organizations more efficient and agile to thrive in a dynamic marketplace.

If this sounds like something that would be helpful to you—or someone you know—download the whole article to learn more.

The one thing that I had not expected was a weekend full of discussions with my friends about the event’s numbers. With close to 90,000 fans on Facebook, Warrior Dash has sold out ten events across the country. The Dash I attended drew almost 10,000 participants in one weekend, at sixteen heats per day and 350 people per heat, and I started to wonder: How do they keep track of their success? How do they measure repeat attendees? How do they keep their unique event vision creative and still mind the numbers?

In my working life, I often think of numbers in terms of success measures. Especially now, with tightened purse strings, metrics are essential for validating customer engagement programs. Often executives ask questions like: How many references are in the program? How often do they participate in requests? What opportunity dollars are associated with the reference activity? Are there gaps in the available reference pool? And it’s up to you to supply the answers and validate your program.

As proven by the Warrior Dash, metrics don’t have to stifle your creative, thoughtful vision. Use the metrics to your benefit. While parameters should be defined, metrics shouldn’t be restrictive in the creative sense. When thinking about metrics for your organization:

• First, consider what makes your program stand out among other reference programs. By knowing the unique identifiers for your program, you can keep the program integrity intact and align your metrics to your distinctive program.
• Second, ask yourself what metrics really matter and focus your energy on achieving the relevant numbers without compromising the program vision. For instance, if your program vision is get dynamic customer references across all verticals, assign a goal for each vertical and then report on how you’re tracking against that goal.
• Third, consider automation. By automating the reporting functionality of your efforts, you can spend more time on the program itself. Having the extra time to keep current program participants engaged and enlist new references will not only help you achieve your goals, but also give you time to carry out your program vision.

When you think about success measures as a tool for protecting your program creativity, you can not only meet your program mission, you can also achieve measurable results.

To find out more about how to maintain your true program spirit and creativity and obtain the metrics you need to support your vision, visit our page on reference marketing.

So, when should you use your data to create a visual representation of your business intelligence? I thinks it depends on two main factors:

• Who is your audience? Are you talking to other analysts, your marketing team, or executives? How much time will you have? What are their priorities? As with any presentation, this should guide how detailed your visualization is.
• Will the visualization make your data substantially clearer? Can you find a visual format that is easily comprehensible? You want the visualization to illuminate your data, rather than obscuring it. If your charts distract viewers from the important insights, causing them to fixate on red herrings, reconsider your visualization.

Because we have more data, faster processing, and more complex data sources, Business Intelligence now has access to a quantity (and quality) of data that was previously only accessible to enormous research firms—or NASA. Making sense of this data is harder than ever, and design can be a vital part of digesting and presenting data effectively. (A recent TED talk did a great job of showing just how helpful it can be.)

IT’s cultural hesitation about “just” pretty pictures is justified: how many times have we had someone draw up an elegant UI on a wireframe, but neglect to involve the technical team in discussions about feasibility and long term flexibility and support? We know that starting with the picture can run the risk of creating unrealistic expectations or ignoring technical realities. We prefer to start with data and the ability to sort, filter, pivot and manipulate it in whatever ways we need to make our analysis.

On the other hand, if I’m a Chief Marketing Officer and I can quickly illustrate—with hard data—my claim that this year’s campaigns have been more effective than last year’s, my CEO is much more likely to sign off on the budget I’m seeking for next year. A dramatically sloped line, intriguingly weighted pie chart, or clear spatial correlation can be stunningly persuasive. What if I could look at multiple campaigns and channels and overlay the impact one has when used in conjunction with another one? For instance, email and a quick follow up phone call vs. a newsletter sent out after a trade show?

If I’m a business owner, good data visualization can give me a snapshot of how my business is performing as well as helping me spot trends and trouble spots more quickly. For the techie in IT, visualization provides validation for my business intelligence initiatives by increasing understanding of them among those who operate more at the business level.

Recently I attended a Seattle Technical Start Up meeting, where Tableau Software presented their method for visualization of data about FAA accidents with various types of birds. The type of bird was represented by a colored circle which grew in size relative to the total cost of the collision with the airplane. At a glance, you could tell which type of bird caused the greatest damage and filter by time of day or type of aircraft, drilling down to the underlying source and raw data to appease their need to see the numbers.

If we can more quickly and clearly understand the vast amounts of data we all are confronted with on a daily basis and use this information to make changes in our business processes earlier on, we’re one step closer to the promised land of analytical enlightenment.

Contact me at brianh@projectlineinc.com if you would like to learn more.

Good business intelligence is invaluable in helping companies decipher the flood of information about their customers. A well-designed, flexible customer dimension is crucial to gathering, filtering, and presenting customer data effectively.

Our article spells out the most important considerations in building or improving a robust customer dimension. We offer recommendations that are relevant for business intelligence challenges shared by startups and Fortune 500 corporations alike. We’ll discuss why you should plan for core business needs, prepare for flexibility, prioritize for swift adoption, and design with the future in mind.

It’s totally free to read and download, so please–take a look, read it through, and let us know if it raises any questions for you. We’d love to answer them in the next installment!

Some participants thought the new title implied too much emphasis on data and metrics, and others were sorry to see the “CRM” moniker go, but I think the change demonstrates the coming of age of Customer Relationship Management (CRM) and the convergence of marketing and business intelligence. The new name, to me, shows that the industry has recognized the need to get a full 360 degree view of the customer.

One of my favorite sessions that spoke to this was by Gartner Analyst Bill Gassman. Called “How Marketing Benefits from Data Analysis and Marketing Skills,” it focused on three major areas: how BI can help with marketing strategy, bringing the business and IT closer together, and the importance of data quality. His presentation described some of the ways that a good business intelligence framework can contribute to that 360-view of the customer by avoiding information silos.

The focus on comprehensive customer insight is especially important in the current economic climate, with tightening budgets; the CEO, CFO, and Sr. Marketing management are all being held more accountable for the return on their marketing spend. They need the information to decide which programs are most effective.

At Projectline, we’re helping our customers get the insight they need by helping unlock siloed data, improve data quality, and manage the whole view of the customer. To learn more, contact me at brianh@projectlineinc.com.

But, like it or not, the meteoric rise of “self-serve” Business Intelligence tools (like Qlickview, Tableau Software, and PowerPivot) shows that these tools are not going away—and maybe that’s not such a bad thing. In fact, I would argue that these new tools will actually be good for the adoption and overall growth and maturity of Business Intelligence in many organizations.

While these tools aren’t a substitute for dimensional modeling, they do serve a purpose and help to drive more investment in projects that show a greater ROI; they serve as a foundation for better collaboration between business and IT by giving the business users tools that help them access data and build their own reports. Looking at how these tools are used, allows IT to get a better understanding of what the business truly wants to measure and can make better investment decisions around data warehousing and decision support systems to serve a broader audience.

For example, let’s say I’m the manager of customer service and I decide the enterprise Business Intelligence tool I’m using doesn’t give me all of the information I’m looking for. Perhaps I’ve seen a 20% drop in customers over the last year—I need to find out why they are leaving. Using my CRM and some Pivot Tables, I can spin up some quick reports that bring in other data sources that I think might be relevant to the recent changes.

If my analysis shows a strong correlation between the loss of my customers and (for instance) a new competitor opening in my region, then I probably want to bring that data into more of a main stream environment and share it across the organization. If the drop seems primarily related to the change in economy, I probably don’t need to invest in a more tightly and costly integrated solution that brings the new data source into my centralized data warehouse. In this scenario, a few simple self-service tools could provide a rapid solution to help me understand some changes in my business (without bothering the busy folks in IT) as well as a barometer on what data/reporting needs should be brought into a more formalized reporting framework.

So there’s no need to be afraid of the more powerful self-service tools. Used correctly, they don’t take the place of data warehousing or integrated intelligence models—they simply help make informed decisions about larger Business Intelligence solutions.

If you’d like to learn more about how to establish a framework for successfully integrating these tools into your current BI environment, contact me at brianh@projectlineinc.com. We’d love to help.

This article explores how businesses can become as agile as their customers through customer intelligence—a way of looking at business that is customer-centric and interdisciplinary. Customer intelligence helps you gain cross-departmental insight into every aspect of technology adoption—from research, to product development, customer adoption experiences, business analytics, marketing, and sales—giving your business a tremendous advantage in the marketplace.

We’ll discuss how you can become a customer advocate, focus on customer value, build an intelligence engine, and know when to engage a strategic intelligence partner. By valuing visibility into the customer experience, you have the chance to build intelligent relationships with customers that drive revenue and increase profits.

It’s totally free to read and download, so please–take a look, read it through, and let us know if it raises any questions for you. We’d love to answer them in the next installment!