Intelligent Metrix

Data to Metrics to Insight to Intelligent Decisions

B2B Lead Nurturing is Not Linear

Lead Nurturing Lead PassIt is much easier and cheaper to work with people that know you than it is to build a new realm.  That is what many marketers and companies are realizing as they shift marketing investment.  Lead nurturing is now more important than ever.  Yet, if you analyze your database, what does lead nurturing look like?  When is a lead qualified to truly enter into the sales cycle?

Demand and lead generation steps have typically progressed from response to lead pass without adequate filtering or analysis that a lead is ready to engage in the sales process.  This has hurt marketing’s credibility in generating real value to the pipeline.  It has put the work on sales to ‘clean’ the database and have them focus energy on leads that aren’t interested or ready for personal connection and may be of lower value than cold calling.  Additionally, some companies try to alleviate this by adding a telemarketing stage prior to a lead pass to personally assess and qualify a lead for the pass.  This can be a costly investment for marketing if again, it is putting leads into this step of the process before leads are fully baked.  Yet, that doesn’t have to be the case.  Properly analyzing and defining leads or groups of leads by their activity within an account can offer sales insight that puts them closer to the opportunity.  This is where lead nurturing can be a strategic effort rather than a tactical process.

Traditional lead tracking reports show a linear funnel from response to disposition within a campaign or program which mimics the linear aspect of the lead process.  In reality, leads have most likely been associated across campaigns, social media marketing interactions, organic web visitations, and even events or interactions with sales and other organizations.  How leads interact, where they go, the frequency, and topic concentration tells you a lot about how ready they are to enter a sales engagement process.  Additionally, compared and correlated to other leads within the same organization, you get a good picture of account readiness and opportunity.

This analysis in many cases is conducted to create target segments as launch pads for new campaigns.  Leveraged within a lead nurturing process, it can be the used as the decision point for when it is best to pass a lead to sales.  It becomes what qualifies the lead to move on vs. relying solely on a single response point on its own or in a linear context.  In fact, analyzed properly, reports and dashboards can be provided to sales that provide a picture of high opportunity areas within their accounts that they may not have seen.  For instance, an up-tic in white paper readership and participating or scanning of social media marketing content on products within an account might provide account managers early warnings that companies are assessing new solutions.  By having a report that provides context on the customer relationship provides sales a greater ability to pick up on the lead nurturing process without having to wait for marketing to pass the lead themselves.

Today, leads are classified as meeting minimum requirements of responding to a campaign and having check boxes of information filled out.  Lead nurturing is really about understanding interactions with your customers and how those interactions are indicators for next steps in the relationship.  Analyzing and recognizing patterns within your contact and account databases is more than identifying segments for targeting new messages and offers.  Used strategically it can be a transition point in your lead pass process improving your ability to generate business and reduce resources and budget through better focus.

Reblog this post [with Zemanta]

Filed under: business intelligence, CRM, Lead Management, , , , , , , , , , , ,

B2B CRM: The Right Contact Mix for Your Customer Relationship

You’ve spent years gathering contacts into your databases.  You’ve implemented a data quality practice that is now starting to give you a solid picture of your universe.  It is now time to classify your contacts.

Invariably, your database is more than just purchasing/decision maker contacts.  All departments have gathered people’s information depending on the purpose.  It offers a window into your business dealings.  It also offers a window on your ability to market and sell.  Just as you consider vehicles, content, and message to deliver to your database, you also think about who you are reaching and who can be converted.

SOA and MDM initiatives are great because they bring together a full picture of interactions with the customer as well as who is part of those interactions.  But, not all contacts are created equal.  Just as not all customers or companies are created equal.  It is the first thing that is considered when determining targeting strategies.  The size of a database is typically determined based on the silo it is intended to help.  Marketing wants decision makers, finance wants accounts payable, customer support wants end users, investor relations wants analysts and media.  By themselves, these data silos serve a purpose.  Together, they can show a picture of where your awareness, message and brand really are.

A good  test once consolidation of data bases is done, or even within your CRM system alone if it receives lists and feeds from other internal sources, is to classify contacts based on their primary interaction with your company.  Everyone in your database has had a reason to connect.  Bringing these reasons into a standardized category will help determine the value they bring to a marketing program, customer relationship, or evangelist role.  Monitoring the ratios of these groups within a cusotmer relationship and firmographic data can give insight into the ability to grow a relationship, if it is at risk, or there is no relationship and the company serves another purpose.

While as marketers we typically look at the entire size of our database to determine if we have enough contacts to convert to leads, if those leads are weighted towards a low number of companies, or they are not the right contacts, then our efforts can be wasted.  With the cost to acquire customers and contacts expensive, having a mechanism to determine when to purchase lists and how much to purchase will refine the amount of resources and budget needed.  In addition, messaging and engagement strategies can be modified to align to the type of relationship outcome you intend.

So, rather than thinking about personas when you need to target, think about them strategically and as an indicator of the strength of relationship with your customer.

Reblog this post [with Zemanta]

Filed under: business intelligence, CRM, Data Quality, marketing operations, , , , , , , , , , ,

B2B Social Media – Has Marketing Effectiveness and Efficiency Improved?

How much effort do you need to put into social media before it pays off in B2B? The answer probably has to do with what you expect from social media in the first place. The problem I see for B2B social media marketing is that instead of 1) increasing marketing effectiveness by facilitating sales and deepening customer relationships 2) making marketing more efficient by streamlining process and resources, it may be doing just the opposite.

Marketing Effectiveness

In it’s ability to facilitate sales and deepen the customer relationship, time and again, marketers and sales are unable to translate awareness and conversation trends in social media to sales. In addition, I wonder if connection trends, comment ratios, and sharing ratios are really anything but another way to track existing customer relationships. I’ve narrowed down marketing effectiveness metrics to four (4) key themes. In each case, I’m looking for improvements due to social media.

  • Improve win/loss ratio – Sales may ultimately be responsible for this metric, but marketing is responsible for lead nurturing which contributes to it. The reality is that the awareness marketing that is happening in social media may not be doing anything but providing another outlet for the same content. Tactics such as white paper promotion and communication of offers may appear to increase leads, but views and registrations may ultimately be with the same people already existing within the customer database. In the end, is the social media marketing tactic really changing customer perception during the sales process to make them choose you’re solution more often? I’m not sure it does.
  • Shorten sales cycle – I pose that the sales cycle may actually be lengthening in social media marketing rather than shrinking. Social media appears to be focused more on awareness building than lead generation. This effort is at the beginning stages of the marketing funnel. In fact, because of the conversational nature of social media, it takes longer to convert a ‘getting to know you’ dialogue to a ‘let’s do business’ dialogue. So, instead of coordinating marketing efforts with sales engagement and the decision process, social media is acting more as a fishing net.
  • Increase sales – Due to an increased sales cycle, you may be losing time to help close a deal. Solely focusing on lead nurturing vs. lead conversion can have the affect of creating a state of purgatory for potential customers. Social media, in theory, should help expand your footprint within your customer base by improving customer relationships. However, all social media marketing is doing today is proving a facelift to existing customer forums, white-paper libraries, and transitioning web content to blog content.
  • Reduce churn – There is much buzz around Twitter’s ability to manage customer expectations and improve customer support. Thus, this translates to reducing customer defection. The issue here is that this isn’t happening in the marketing organization. This is a function of customer service. Where marketing fails is that customers are focused on their business, not yours. Conversations in social media marketing today are still more focused on ‘look at me Mr. Customer’. All the customer wants is for you to look at them. It is an effort for customers to utilize and participate in social networks and gather information in social media. There are still too many places the customer has to go to interact. We make it difficult to solidify relationships by managing multiple properties and outlets to connect.

Marketing Efficiency

There is a real hidden cost to utilizing social media for B2B marketing. It is the cost to do business. Due to the number of ways you can connect to customers, it requires a significant amount of effort to cover and manage all the properties. While you can write a single blog and push it out across multiple communities, the lack of diversity in conversations may hurt more than help. Each community probably has a different DNA. One message is not going to be relevant for all. Thus, you have to produce more content across more topics to be effective.

Another aspect of inefficiency is the art of the conversation. For social media to work, it requires a de-centralized communication web to interact with customers. Sales already has this in place as it is what they do every day. Marketing is smaller and has less resources. This puts pressure on the organization to have personalized attention to carry on a conversation. Marketing needs the ability to respond to comments, participate in groups in a conversational manner, and organize discussions and groups around a multitude of topics that customers are interested in. If you go to forums today, there are few that have real conversations happening. Mostly you see blogging and promotional content being posted. This is because it takes a huge amount of bandwidth to truly be interactive with your customers.

Lastly, there is inefficiency to how marketing manages relationships across multiple social media platforms. Again, the number of venues creates chaos in the ability to recognize a single customer. Efforts are duplicative and can create problems in a cohesive conversation and message. Marketing technology needs to be streamlined to better manage relationships.

What’s Next?

As social media marketing has been the buzz and huge shifts are being made to transition and leverage its potential, B2B marketing organizations need to be mindful of what their business charter is and how they meet their goals through effectiveness and efficiency. Social media is just part of the mix, and as with any marketing effort, you don’t want to put all your efforts into one tactic. If not properly monitored against key business benchmarks it can quickly de-focus your marketing efforts and lead to poor performance.

Reblog this post [with Zemanta]

Filed under: business intelligence, Performance Management, , , , , , , , , ,

Social Media: Back to Spreadsheets

It’s a dirty word right now – spreadsheets.  IT departments want to remove our dependence on spreadsheets and convert us over to a secure, controlled, shared, and robust analytic environment.  I would love that!  But, I have a problem, social media.

I’m managing more properties and content that is outside the realm of my corporate environment but I still have to report back and show how it is doing.  The only way I can do this is by using several analytic tools across multiple properties.  I grab the stats I need and punch that into a spreadsheet.  Then, I go to my web analytics reports, grab those stats, and consolidate them with my social media data on my spreadsheet. After that, I consolidate my lead metrics with my internet metrics for a 360° view of my marketing efforts.

It is all very time consuming and open to data entry error.

Business Intelligence is great to track internal process, but it is doing nothing to help track activities outside the corporate environment.  So, I’m stuck with spreadsheets.  Can you help?

Reblog this post [with Zemanta]

Filed under: business intelligence, Performance Management, , , , , , , , , ,

Business Intelligence: Decisions, Decisions

Business Intelligence is all about supporting business decision.”

How many times have you heard that?  It’s become the standard mantra.  It is so ubiquitous that I don’t think anyone questions anymore the validity of the statement.  It just is.  However, this is probably the hardest part to facilitate when building out you business intelligence practice.  Facilitating decisions is what makes BI stragetic.

Just what is the business decision? What does a business decision look like?

Elements of a Business Decision:

  • Purpose:  drive a business outcome – ex: revenue, shareholder value, profitability, market share
  • Position:  leads a company, division, department
  • Point in Time:  transition along a process or environment

A typical approach during the business analysis phase for BI is to at business decisions across a business process and where questions are asked to change behavior in that process.  Although, the difficulty with this level of granularity is that it is too deep.  These transition points are tactical.  Intelligence across this process and at these decision points is important, but you don’t get the strategic value of BI at this level.  You need to look at the outcome of the process and provide a platform that supports the decision of what to do next.  This is the unstated question.

Let’s take an example.  Sales management will always want a perspective on the pipeline and forecast.  This shows them how they are meeting their numbers quarter to quarter.  However, outside of conversion and volume, there are business decisions that sales managers need to make.  Should they adjust their territories to capture new opportunity or shore up existing business?  Are there changes needed in commissions to incent sales people along certain products and services to improve profitability or revenue?   BI can lead sales management with insights that will guide them to optimize their processes and management rather than just data.

Purpose:  market share, revenue, profit
Position:  sales
Point in Time:  aligned to quarterly pipeline and forecast

To align BI to the business decision it is important to include executives in the discussion.  Get beyond the reports they want to see and ask the question about how they manage their business.  Walk through scenarios of what they ask as changes in the market or the business arise and how information can help them make a decision.  The better able you are to see how they manage their business, the more valuable the BI practice will be to supporting the business.

Reblog this post [with Zemanta]

Filed under: business intelligence, Performance Management, , , , , , , , , , , ,

Why Business Intelligence is So Difficult

Reading the buzz on the Jim Davis’s presentation at SAS Global Executive Forum, what it made me realize is that if as an industry we can’t agree on what Business Intelligence is or Business Analytics, how are we supposed to make sense of it in implementation?

business intelligence confusionYou have analytics players, enterprise application vendors, business process consultants, and analysts all trying to sell the ‘hype’ of a better way to analyze your business and makes decisions.    SAS wants to sell their analytic solution that really pioneered data mining in businesses.  Oracle and IBM wants to push dashboard solutions that links to business processes and their enterprise applications.  Gartner that tries to tie together people, process, and technology but is really is focused on what technology to buy.  Then, you have consultants that are trying to help you implement the technology even as they document your processes.  The problem is that it’s all boiling down to the one with the best tool wins.

Enter in the ‘Business’ and now you have a problem.  All they want to know is how they can meet their business objectives.  IT is trying to sell the solution and make them understand the technology, and the business glazes over and can’t figure out what to focus on.  I’ve sat in these discussions where IT tells me, “You tell us what to do, we’ll do it.  Don’t worry about the solution.”  It is open ended.  This leads to IT unable to work towards tangible goals and results.  The business walks away frustrated, projects run from months into years, and original budgets are thrown out the window.  I liken these projects to Boston’s Big Dig.

Neil Raden provided a perfect way to get through the fluff and hype that surrounds analytics and business intelligence. See article From BI to Business Analytics, It’s All Fluff

“I don’t like the term business analytics; it doesn’t tell me anything. Frankly, I think business intelligence as a term is downright laughable, too. What does that mean? Is integrating data intelligence? Is generating reports intelligence? Maybe its informing, but isn’t intelligence something you HAVE not something you do? Does doing what we call BI lead to intelligence, or just some information? A long time ago we called this decision support, and that gets my vote.”

So here’s my take on what steps to take when and how to venture into BI and analytic solutions.

Steps:

  1. What decisions need to be made?
  2. At what point in our business and business processes are these decisions made?
  3. What information is needed at these points?
  4. How should our applications and data provide this information – triggers or visualization?

See the steps?  It starts with the business decion and ends in the technology.  So, when you begin to review vendors and solutions, make sure you have steps 1,2,3 in mind before you determine how to solve step 4.

Reblog this post [with Zemanta]

Filed under: business intelligence, Decision Cycle, Performance Management, , , , , , ,

Who I Want at the Business Intelligence Table

Go and look at any guide on implementing Business Intelligence (BI) and invariably executive leadership is touted as a must.  I couldn’t agree more.  In the end, the product of BI is to help them manage the business and make the company successful.  But, the reality is that they look to their department managers and IT teams to work out the details.  Show them the investment and ROI, then get busy on delivering it.

So, what next?  Who do I want on my BI team?

Rather than looking at this in terms of titles and functions, let’s look at this in terms of areas of expertise and levels of project responsibility.  They reason I do this is because as much as process is the typical focus for the typical IT project, BI is a big picture endeavor.  Process will show where data originated from and how data is defined, but it won’t always be a direct linkage to the business objective.  Example:  Predictive analysis might focus on anticipating customer defection.  The process is a component of the customer experience, but the analysis crosses multiple processes.

Business Side:

  • BI Leader:  Strategic thinkers with deep expertise across department practices.  This is where you get bench strength for the project.  You need these strong generalists that see the big picture of customer relationship, financial management, or operational functions as they pertain to business objectives.  These people have been there and done it in some shape or form.  They may have even moved across departments and shifted across areas of expertise.  They know the type of information necessary to be strategic, improve process with information, and how to focus and prioritize information needs.  Where to look: Manager and director positions close to the executive sponsor that have proposed or driven change.
  • BI User:  Analytic champions that have mastered company information providing a range of analysis.  BI Users will be the real developers in the details of the requirements.  They know the company data better than the people that designed the warehouse to manage it.  They can tell you the limitations they have in providing analysis that is meaningful.  Champions have a wide array of analytic techniques from the highly simple to the more complex.  In fact, they could fulfill analytic requests regardless of the department.  They are the scientists in the company.  Where to look:  They support the successful managers, directors, and executives that use data to influence business decisions and priorities.
  • BI Business Analyst:  Business technologist that has experience across multiple types of implementations.   Technologists have a pretty good understanding of how to optimize and fulfill business needs with technology.  Many times they are considered the liaisons between the business and IT.  However, this is more than the note taking of requirements and passing along to IT, project managing, and then ensuring priorities are met.  The technologists are versed in their businesses.  They have migrated from a business role to technology focused role rather than starting from IT and moving to the business.  In addition, they have a depth of technical knowledge and know how to converse and validate recommendations and solutions from IT.  Where to look:  They have most likely been through a couple of solution implementations or data integrations and have a key role in establishing requirements as a business lead or as the lead project manager and business analyst.

IT Side:

  • BI Leader:  Strategic thinkers with deep expertise in driving business outcomes through solutions.  This is the person that talks about the business and rarely about the technology.  They focus on  the strategic implementation and adoption of technology for competitive advantage.  While experts in solutions and infrastructure, the real focus is on efficiency and effectiveness of the business.   They ask, “What problem is the business facing and how do I help?”    They are attuned to company success.  For BI, they need to have a perspective across enterprise applications and data warehouse management.  Where to look:  These are IT leaders that are close to business executives and are goaled on supporting business outcomes.
  • BI Solution Provider:  Solution champions that perfectly unite applications with their back-end information.  They recognize how data relates to the business process as well as the next step of how people use data in the process and to manage the business.  Solution Providers are strategic in their approach to solutions and differentiate between requirement fulfillment and business enablement.  They do what their title says, they come up with solutions rather than just implement technology.  When building applications, data modeling is not far from their thoughts and data warehouse teams are tightly involved in strategy and design.  This is the person that is in the nuts an bolts of best practices of solutions.  Where to look:  These are the people that you turn to for application and data integrations due to M&A activity or legacy system integration and migration.  They spend as much time with the business as they do with IT.
  • BI Implementers:  IT technologies with deep expertise and range of experience in their tools.  BI Implementers will be many spanning across application development and data warehouse.  While not typically in contact with the business during business analysis and design, they are critical to proper development.  They will have silos of expertise in user interfaces, application infrastructure, data warehousing, data management, systems management, data quality, ETL, and database architecture and modeling.  Depending on the size of the company, these silos of expertise will be supported by one or more people.  They will either perform the technical development themselves, or have a team that is experienced to do so.  Where to look: IT Solution Providers that recognize deep strengths in their teams for a strong implementation bench. 

The Often Forgotten One:

Database modeling is one of those aspects of application development and data warehousing that is often left out.  Modeling is a critical factor of success in BI because of its ability to make analysis very easy or force unnecessary issues in performance and programming work-arounds, particularly within ETL and the user-interface.  I can’t stress enough the value of having and expert modeler on hand.  So, if you don’t have a modeler on staff, consider how to fulfill this vital role at the beginning of your design phase.

Using these profiles as a guide to build your team will set you up to successfully design and implement your BI practice.  In addition, you have the ability to see the how the Business and IT balance each other out in experiences and expertise to allow for a good working relationship.  These profiles should also give you a perspective of what, if any consultant or contractor help you need.  The key is to recognize that building your BI team is not unlike hiring an employee and that the more breadth of expertise and experience that person has, the better off you are in the long run.

Filed under: business intelligence, , , , ,

Starting Your Business: Data From the Ground Up

data managementIt is easy when starting up a business to think about selling first, marketing and database management later.  Afterall, revenue is the most important thing to focus on.  Though, once you get over the hump and begin to groove, you realize that data is important.  Now you have to sort through it and it feels worse than diving into list of 300 emails in your daily inbox.  Well, if you have a method to deal with your email inbox, create one for managing customer and contact data.

Here are some simple things you can do up front to stay organized and be better prepared when you are ready to look at and manage your customers and the business in depth.

  • Be consistent about how you collect customer data – There are usually several layers to the importance of customer information elements depending on your relationship.  What you want to do is determine the information that is most critical and collect this consistently across all methods.  Keep in mind that what is mandatory to transaction may be different from what you need to follow-up with customers after a purchase.  So, make sure that you take this into account at the point in time you collect the information.  It is harder and more costly to collect after the fact.
  • Save data elements into dedicated fields – The biggest issue I find with new businesses and small businesses when they need to convert to more robust systems is that data elements are merged together into a single Excel cell.  When collecting contact names, break apart the first and last name into separate fields.   Do the same for addresses having fields for street address, city, state, country, and postal code.
  • Determine what platform has the Master data – The second biggest issue when migrating customers to a robust system is the inability to determine which record is the most valid of duplicate entries.  If you are saving contact and company information between your mobile phone, laptop, website, and company server, which will you consider the single source of record?  Once you determine this, make sure you sync your lists to that source.  I recommend you do this weekly at the least and use your primary server.  Then, include the database in a weekly back-up process.
  • Save, Save, Save – You may have caught this recommendation in the previous bullet.  Backing up is critical.  It is mandatory.  I’ve watch small businesses loose business critical information because they didn’t back up or back up often enough.  There are easy services today that make backing up our information simple.  At the very least, invest in a USB storage device and plug into daily when you sit down and get to work.  Before you do anything, back up.  Make it a habit.

Managing your customer and company information does not have to be difficult or cumbersome.  With a little forethought, when you business gets off the ground and you are ready to invest in better platforms and reporting, you will have a great foundation to do so.

Reblog this post [with Zemanta]

Filed under: business intelligence, CRM, Data Quality, , , , , , , , , ,

Cool Data Visualization – What is That?

Want to help your organization optimize operations, extract market opportunity, see what customers think?  Provide a visual representation in a single slide that tells your senior executives what is happening and what to do.  That is, if they can understand it in a milli-second.

There are a lot of really great algorithms that are creating interesting visual presentations of behavior, influence, and connections across people and topics.  The problem is you might as well be looking at fractals for all the business insight you gain.  It may provide perspective for the resident math geek, but for the average business executive it is just modern art that needs further interpretation.

I remember in college when I first started programming mathematical equations to model data and played with fractals.  It was exciting, creative, and helped me to link data with a tangible result versus a simplified equation or answer.  I used to put fractals up on my website like works of art.  I even included a link to input random numbers for others to create their own.  It was so cool!  Was it practical?

Don’t get me wrong, I love data visualization obviously.  It can simplify very complex analysis to gain insight faster.  What I’m struggling with is needing the ability to connect data visualization with executive intuitiveness.  Heat maps, network graphs, and the variety of data maps I see being generated today are a far cry from what I would bring into a budget meeting let alone show to board members.  More time is spent explaining what executives are looking at than having conversations about business objectives and investments.  It is also not just executives.  Business managers and directors need to understand the business as well.  Pretty is nice, but value is better.

The other aspect that of today’s data visualization leaps is that it disassociates the business from the information.  If only a small group of geeky mathematicians and programmers understand the data, it creates a mysticism that can lead to distrust of information.  If people don’t understand it, they don’t learn, and they don’t improve.

What I hope we can do as really smart statisticians, data analysts, and programmers is make the connection between information and visualization so that it further democratizes insight and empowers our business rather than mystify.

Reblog this post [with Zemanta]

Filed under: business intelligence, , , , , , , , , , , , , , ,