The tradeshow pitch; 30 second training guide

Best practices for your 30 second elevator pitch:

Think in terms of 3 bullet points

  1. What is the problem in the market (why does your product/service exist)?
  2. How do you solve that problem?
  3. Why is your organization unique?

If you focus on these 3 things, you will have a concise pitch delivery. Other aspects of getting your pitch down across your entire organization:

* Recording the pitch
* Components of a good pitch
* Developing a good pitch
* Testing your pitch
* Customizing your pitch
* When to give the pitch
* Common pitch mistakes
* Capturing the pitch
* Measuring the pitch for individuals
* Measuring the pitch for groups
* Coaching the pitch

Segmenting Titles to Power Account Based Marketing (ABM)

The days of succeeding with email campaigns while sending a generic message are done.  No one disagrees with this point.  Everyone sees response rates dropping.  The answer?  On this point, people in the know also agree:  The answer is segmenting your audience and sending a targeted message.  The debate approaches when discussing how to accomplish segmentation.


Much has been written recently on Account Based Marketing (ABM).  Simple concept: determine as many attributes you can about your target accounts. Use those attributes to pick the best companies to reach out to. Great! This IS segmentation, however, there is a brilliant opportunity here, within reach, that is being overlooked.

The opportunity is segmenting your prospects (and clients) titles to more effectively target market with them.  Again, no one disagrees that this should be done, but how is it currently being done?

Currently we see people building lists of 100’s (or more) phrases to match and segment.  Example:  “Marketing” OR “Marktg” OR “Mrktg”.  These lists get long and have some inherent flaws:

  1. The lists are NOT comprehensive.  Their will always be exceptions.  There are some amazing, talented, consultants that have their “golden list” of match phrases like this.  The problem is that you will need consultants to maintain and modify if you need changes.  Not sustainable or efficient. This is a brute force approach.
  2. If you segment on a department like Marketing, you will miss the title level, such as VP.  Conversely, if you segment on level, like VP, you miss the department.   If you try to segment on both, now you have multiple lists of 100’s of phrases that again, it grows into the 1000’s if you want it to be comprehensive.
  3. Analyzing connected relationship becomes unmanageable. For example:  Knowing that you have a VP of Marketing that influences two Directors of Marketing?  You can’t establish this connection without multiple attributes that have been pre-calculated.
  4. Having a single attribute like Title Level OR Department makes the logic crazy complex.  Trying to build a campaign that includes the “Top Marketing Contact”,  “Top Sales Contact” and “Top Operations Contact” is only a dream when you only have a single segmentation bucket.
  5. It’s not fun. Complexity should be hidden and the average campaign manager should be able to set up brilliant campaign.  Democratize it.

After 14 years of data mining and working with massive amounts of contact data, I’ll fast forward and give the answer:  If you segment on both DEPARTMENT and TITLE LEVEL, you can accomplish, I’ll say it again, brilliant, segmented, campaigns that are easy to execute.  Watch the video for a nice visual walk-through of the concepts.

Top of the mind: steps to Cleaning your CRM

“What is the first step to take to clean up your CRM data”?

Nearly everyone I pose this question to gets it wrong.  The typical answer is “dedupe the CRM”.

This list was for a client:  A stream of consciousness cut & paste from an email.  He needed something to discuss with his team.  He no longer believes dedupe (alone) will solve his data problems.

The real list is longer, but you only get that if you are my client.

  1. Silo Identification – Identify the sources of data.
  2. Structured Capture – Pool data from CRM, lists & databases.
  3. Unstructured Capture – Extract & Datamine.  Email archives,  etc.
  4. Data Assessment – Getting the facts about the data.
  5. Assessment Review –
  6. Consultation –   blah blah
  7. Data Standards Plan – Design a strategy for future data standards.
  8. Data Normalize – Standardize according to Data Plan.
  9. URL Fill – Complete URL’s to disambiguate target objects.
  10. Data Mapping – Define and align data from all sources.
  11. Concatenate Silos – Combine into unified destination
  12. Duplicate Detection Rules -Define what constitutes a duplicate
  13. Resolution Plan –
  14. Scoring Plan – Develop weights for conflicting data sources
  15. Silo Merge – Merge data according to weights in scoring plan
  16. Automated Dedupe – auto
  17. Duplicate resolution – manual
  18. Data Actions – what happens w/ data
  19. Clean Review
  20. Address Correction
  21. Company Profiling
  22. Email Fill
  23. Enhancement Review