All Things Data

Customer Retention

Retaining customers is fundamental to any organization and it is more so today.

A useful technique in the customer retention effort is to measure a customer’s relationship with your organization.  This measure can be expressed as an index. This index can help you identify customers, well before a milestone, such as a renewal date, that might be a risk of leaving or cancelling.

The index can be developed based on several important customer activities, attributes, characteristics and trends.  These can include

• The products/services purchased
• Length of relationship
• Purchase activities and history, including recency, frequency, and monetary value
• Degree of participation in events, i.e. conferences, seminars, webinars, user groups
• Customer service usage
• The number of contacts from the customer organization using your products/services
• A change in the key decision maker(s)

Your index should include the trend of activity over time compared to previous periods.

Various names have been applied to customer retention indices.  These include Customer Relationship Index, Member Retention Index, and Danger Index.

Whatever you may want to call it, a relationship index can help you identify possible customer attrition and give you the opportunity to work with your customer to retain their business before it is too late.

Top Priorities: Growth and Business Intelligence (BI)

According to a recent Gartner study, CIOs see their Number One business priority for 2013 is to increase enterprise growth.  Along with growth, CIOs see their Number One technology priority being Analytics and Business Intelligence (BI).

Chances are you have similar priorities to harness and use your data for meaningful analysis to help guide and grow your organization.

The challenge is how to get this done and to do it within a reasonable budget. 

Our Blog, AllThingsData.com, focuses on practical approaches to harnessing and using data.  Take a look at the various posts.  If you would like more details on any of these ideas, please let us know.  We will be glad to help.  Feel free to contact us.

Also, over the next several posts we will outline additional practical steps for getting the most out of your data. 

Make sure to use your data to help you reach your goals.

Discover Data Quality

We are often asked to help with data quality issues. 

Data quality efforts are closely tied to important business needs.  Accurate, consistent, rationalized and coordinated data records are keys to a useful database, a database that can be employed to help reach business objectives.

One of the most obvious indicators of data issues is duplicate records.  This can include duplicate contact records, as well as duplicate organizational location records.  In addition to duplicates, there are several other dimensions of data quality that exists in a database.  These include the accuracy, completeness, timeliness, interconnectedness and usability of the data records.

To help our clients to get a full understanding of their data, we suggest undertaking a Data Discovery.  This involves

* identifying all the data sources that are needed

* profiling the data from all data sources, to identify data characteristics and issues

* determining what data actions are needed

* planning how to work with the data to meet the underlying business goals 

Today tools like SingleVision® are available to help undertake effective, practical and affordable Data Discovery.

Improve Access to Important Business Information

In our work helping clients to develop and use meaningful data for analysis and action, the issue often arises as to how to effectively distribute this insightful information to the various people within the organization.

Many organizations today are using Microsoft^®SharePoint^®for collaboration and communication.  However, many SharePoint implementations are not actively or enthusiastically used.  This is frequently because of the lack of useful information available through their SharePoint system.

We have seen how SharePoint implementations can be made more useful and productive with the addition of meaningful marketing and sales data.  Various people within an organization can have timely access to important information to help effectively do their work.  Permissions as to who has access to what data can be controlled.

We suggest that you should start practically in the delivery of data through your SharePoint system.  Start with basic libraries and reports.  Then, as you expand your SharePoint capabilities, walk down the path of adding Business Intelligence functions, including Dashboards, Scorecards, and Analytic Charts and Grids.  As you proceed, you will gain feedback from the users of the data.  You will also be able to expand your SharePoint knowledge and skills.

Furthermore, this approach will enable you to evaluate, determine and expand the back-end data that is needed by your users.  Often that data will be developed by matching, linking and correlating data from various sources utilizing a data integration tool like SingleVision^®.  That data might also be needed to be organized into an actionable Data Framework for efficient analysis and action.  The quality, accuracy, timeliness and availability of your data is of critical.

The key is to start practically distributing actionable information, gain feedback, build your data competency, extend your SharePoint skills, and then expand over time the depth and sophistication of the delivery of data.

Data Quality for All

We have submitted several posts about the importance of data quality.  Ensuring that your data is accurate, organized and accessible enables better analysis, strategic decisions and tactical actions.

Recently we attended Gartner’s Webinar called “Best Practices To Ensure BI Success Through High-Quality Data.”  Ted Friedman, Gartner VP Distinguished Analyst, did an excellent job in articulating the benefits of data quality initiatives, along with providing ideas for building organizational commitment for data quality.

A great deal of data quality discussion today focuses on how large organizations can organize to improve their data quality.  We know that smaller organizations have the same issues.  Disorganized and inaccurate data can impede proper analysis and hamper effective action steps for any organization.  Small and midsized businesses (SMBs) need to recognize how important data quality is to them.  As such, it is important for those organizations to properly scale their data quality programs to their needs.

SMBs need to commit to Data Quality.  Data quality programs can be managed in SMBs with practical tools like Microsoft Access, Excel, and SQL Server, along with a practical data integration tool like SingleVision®.

Link Related Organizations to Retain and Grow B2B and B2I Customers

The old sales adage is that “your best prospect is your current customer.”  Today this is especially the case, concerning organizations, and their contacts, that are related to your current customer.

It is important to identify within your databases the organizations and their contacts that are related to each other.  This will provide you with valuable sales retention and growth opportunities, including

• Widening your communication network within your customer organization
• Providing additional contacts to help retain existing business, as well as develop new business.
• Expanding your sales with your current customer
• Identifying cross selling and up selling opportunities
• Identifying organizations and contacts that can be approached with references from a related entity

The key here is to identify and link organizations and their contact records together, across all of your data sources, with Common IDs.  This way you will be able to view the data together.  Views should be available to the Sales and Service teams in their CRM systems for their efforts, along with Marketing for analysis and data mining.

Remember, your best prospect might be related to your current customer.

If you need assistance in linking related records together to retain and grow customers, consider using SingleVision®.  SingleVision will match and link records, along with assigning a Common ID to keep the records linked.

Measuring Marketing Outreach Success

In order to properly analyze and measure the success of a marketing campaign, the resulting transactions must be assigned to the outreach activity that is believed to likely to have influenced the action.

For the analysis to be efficient, the organization of both the outreach and the transactions data is important.  One example would be a mailing list, utilizing keycodes that represent the offer given to the contact in question.  Sometimes a respondent will include the keycode of the offer, often they will not.

Most frequently when a customer does go forward with the offer, be it attending a meeting or purchasing a product, the outreach record and the transaction record remain independent, with no straightforward link between the two.

To link transaction records to outreach records, some matching may be necessary.  The business rules for linking these records will vary in each case, but will often rely on the matching of the contact’s name in addition to some other piece of information to confirm that they are not different people with the same name.  The matching algorithm may give varying confidences on the records to be considered a good match.

For example, offer AB1 was mailed to 1,000 people, and, based on matching the mail/outreach file to the transaction file (specifically the transactions in question), 50-60 customers went forward, depending upon the match confidence level to be accepted.

The analysis may then be taken a step further to determine the demographic of the customers that went forward in contrast to those that did not.  This may affect what “type” of customer is mailed a certain offer, as some evidence may show which campaign is most effective for any given variety of contacts.

When marketing campaigns are properly analyzed, the campaigns that follow will benefit from the intelligence and the insight gained.  Over time campaigns will become more effective, garnering higher percentages of success, and saving time and money.

Data Management and Senior Management

A recent article in Advertising Age, “When CMOs Learn to Love Data, They’ll Be VIPs in the C-Suite” caught our attention. We thought our readers might find this insightful.

The article sites a Gartner study that projects that by 2017 the CMO will “spend more money on information technology than the chief information officer.”

Furthermore, the article projects that CMOs will have to “harness customer data and leverage it.”
Forrester analyst Josh Bernoff is quoted in the article saying, "The only sustainable competitive advantage is knowledge of and engagement with customers."

All organizations face the challenge of harnessing and leveraging their data to enable them to reach their goals.

The key first step is to recognize the importance of harnessing data to gain valuable information and insight, and then committing to do something about it. Once committed to the task, today there are practical tools and processes for the Executive to plan and implement the data integration that is needed to harness and leverage data.

Foundation for Sucessful Data Analysis

In these challenging economic times there is a greater need for data analysis to understand what is going on and to determine what to do about it.

There are a plethora of data mining and business intelligence tools on the market today.  Even Microsoft’s SQL Server has business intelligence multi-dimensional data cubing and data mining algorithms built-in as part of its capabilities.

Still, while there are lots of great analysis tools available, it is a fundamental step that you need to first have your data properly organized to gain the benefit of these tools.

For example, if you are analyzing transactional data for multi-entity organizations, the first step is to identify and link all of the separate, but related entities and individuals that are part of the same organization in order to get the complete analysis of an organization.  Also, the data needs to be organized in an efficient manner, so that the analysis tools can work in an efficient manner as well.

Further, a continuously updated data framework is going to enable analysis on an on-going basis and not just a moment in time snapshot.  Without first organizing and coordinating the data, you either will be unable to perform the necessary analysis or your analysis will be incomplete and inaccurate regardless of the analysis tool.

Master Data Management and Rightsizing the Business

In these difficult economic times, it’s important to cut expenses where ever possible.  But how do you know what and how much to cut?

The answers are in your data.

Your data can tell you many things such as:

1. How many customers and prospects that you have?
2. How much revenue by customer, sales territory, and market segment?
3. Where your customers and prospects are located?
4. How effective are certain marketing campaigns?

The answers to these questions and many others are the keys to making decisions regarding the allocation of resources.  Here are some examples:

• Knowing the proper number of customers and prospects and current and potential revenue by markets or territories lets you know how many sales reps, service personnel, service locations, and other expenses that can be consolidated to manage profitability.

• Knowing that someone you sent a direct mail piece has responded either by mail, by phone, through your website, or in-person is critical in understanding whether the campaign should be continued and how much budget should be allocated to future campaigns.

However, there are many challenges to utilizing your data to get the answers to these types of questions.  Here are some of the challenges:

1. Multiple records exist for the same or related customer or prospect entity or contact due to multiple contacts, multiple locations, lack of data uniformity for organization and contact names, and data entry errors for the same entity or contact in your data files.  This makes it difficult to properly report counts and eliminate duplications.  Over counting may result in a missed opportunity to reduce expenses.

2. Information is contained in separate data files such as the initial mailing campaign file, and the related responses by the mail, the web, by phone, and in-person.  The respondents may use different representations of their contact and organization names for the different response vehicles.  This makes it a difficult task to track the initial mailing with the actual results.

Customer Data Integration or Master Data Management software can help properly count the multiple representations of the same or related entity or contacts and correlate records that are contained in separate data silos through matching algorithms.  With the matching and linking via the software’s numbering schema, proper counts can be generated and information from separate data sources can be queried.  This information can help determine the maximum expense consolidation to manage profitability.