A Perfect Demo Environment

 

Have you ever said or heard:

 

“Sorry, I don’t have an example like that in our demo system…”

 

“No, we can’t show that workflow – this is a demo database…”

 

“Our demo environment isn’t up to date – that’s why this feature isn’t working…”

 

“No, I don’t have good data to show in this report – no data, in fact – sorry…!”

 

“That report hasn’t been built for our demo system – but trust me, it’s terrific!”

 

In your demos, how often do you find you are apologizing for an inability to demonstrate capabilities, complete workflows, or present compelling results and reports? Far too often, in many cases!

 

A perfect demo environment enables you to show what you need to show, clearly and convincingly. No apologies, no excuses. Accordingly, here are some recommendations for demo environments to make your demos as crisp, compelling and successful as possible.

 

What’s in this article for you? A lot!

 

-       Demo = Fake!

-       And Don’t Label Things “Demo”

-       No Obviously Fictional Names

-       Include Problems, Exceptions, and Opportunities

-       U.S. vs International

-       Market Alignment

-       Market Maturity

-       Who Am I?

-       Be a Customer

-       Keep It Current

-       Refresh or Reset

-       Availability

-       Performance

-       Surprise – No Internet Access!

-       “Trust Me…”

-       Screen and Projection Woes

-       Mini Mouse

-       Infrastructure Checklist

-       A Perfect Demo Environment

 

You can find the full article here: https://greatdemo.com/a-perfect-demo-environment-never-stop-learning/ 

 

Enjoy!

What Happens If You Train an AI Engine with…?

 

What happens if you train an AI engine with poor data? 

You get Artificial Ignorance!

 

What happens if you train an AI engine with biased data? 

You get Artificial Influence!

 

What happens if you train an AI engine with too little data? 

You get Artificial Inexperience!

 

What happens if you train an AI engine with narrow, non-best-practices data? 

You get Artificial ineptitude!

 

What happens if you train an AI engine with worst-practices data? 

You get Artificial Inferiority!

 

What happens if you train an AI engine with ridiculous data? 

You get Artificial Insanity!

Demo Storylines: Journey, Destination, or Both?

There’s a lot of discussion today about storytelling in demos and related sales activities. Many software vendors talk about “The Journey” or “The Customer’s Journey” as a storyline. We need to ask ourselves, however, what is important for your prospect or your customer?

 

Is it really the Journey, or is it the Destination, or possibly Both?

 

What’s in This Article for You?

 

-        What’s the Difference between the Journey and the Destination?

-        It’s All about Value

-        When It’s Not the Journey

-        When It Is the Journey

-        When It Is the Destination

-        When It Is Both

-        A Matter of Perspective

 

You can find the full article here: https://greatdemo.com/demo-storylines-journey-destination-or-both/ 

 

Enjoy!

“Supposing is good, but finding out is better.”

“Supposing is good, but finding out is better.”

– Mark Twain

Just because all your existing customers suffered from X, Y, and Z doesn’t mean that your next prospect has the same challenges: Be aware of expectation bias when doing discovery!

Data – Information – Knowledge – Wisdom: Where Are You on This Spectrum for Discovery?

Here’s an example of the DIKW progression – contemplate sailing in the ocean:

 

-       Data: The wind is blowing at 30 knots.

-       Information: The forecast shows deteriorating weather and there are already large white-capped waves.

-       Knowledge: The conditions might be too much for our boat.

-       Wisdom: Let’s wait until the winds and seas have abated.

-       Additional Wisdom: And in addition to our lifejackets, let’s carry an emergency raft with a radio, food, and water.

-       Deep Wisdom: My wife says to me, “How about we fly?”

 

And here’s an example regarding doing discovery:

 

-       Data: Uncovers and explores pain (Doing Discovery Levels 1-2).

-       Information: Uncovers and explores pain, impact, and tangible value (Doing Discovery Levels 3-4).

-       Knowledge: Uncovers and explores pain, impact, tangible value, and reengineers vision. Applies these skills to the broad range of prospects across the Technology Adoption Curve, “burn victims,” disruptive and new product categories, transactional sales cycles, and other scenarios (Doing Discovery Levels 5-6).

-       Wisdom: Integrates, aligns, and leverages these skills into a cohesive discovery methodology (Doing Discovery Level 7).

 

Where are you on this spectrum?

 

Uplevel your DIKW with the Doing Discovery book and training!

 

https://GreatDemo.com

 

https://www.amazon.com/Doing-Discovery-Important-Enablement-Processes/dp/B0B8RJK4C2/