Building data dashboards for customers
I just saw a blog post on Seth Godin’s blog recommending that companies build data dashboards to help track usage. It is right on, and the short post is a worthwhile read.
About 1 year ago, I was asked to evaluate a tech company for a significant investment, and I was so impressed with their data tracking dashboards used that it was clear they really were thinking straight about their business. They were managing/selling text services in Europe, and their control center was impressive. They had a tracking dashboard that monitored sales close to real-time, and compared current results with historical data (and statistical deviations) in an easy-to-see, visual graphic. They could tell very quickly if problems occurred with their technology so they could take decisive action quickly.
Regarding equipment simulations, a few years ago we built a simple tracking software program (SimTracker) and our clients love it — they can see in real-time how their demos or training are performing. Our interface is pretty simple, but then we also let clients download the data as CSV if they want to do more involved analyses. The more savvy marketers can create a ‘mini-focus group’ by serving several versions of a piece and seeing which performs best compared with their goals, based on real user behavior rather than what the group thinks the researchers want to hear.
In many of our industries (which tend to be around manufacturing), however, we’ve found that our prospective clients sometimes don’t value this because it seems web/tech companies are not doing a good job of saying why such tracking data is useful, and how to apply it effectively in marketing campaigns.
Product simulation for cross-selling and up-selling
I just ran across an interesting blog post entitled “Measuring and Improving Cross-Sell and Upsell” at GetElastic.com. It gives fascinating numbers and insights about existing online retailers’ current abilities to cross-sell and up-sell products. What struck me is how well product simulation covers all of the take-away messages:
- “we think you’ll also love…” — by putting products in real-world situations, you can expose customers to related products they may not have considered, just like the “we think you’ll also love…” items currently tagged onto shopping cart items.
- Quoting Mike Svatek’s webinar of effective merchandising on Elastic Path, the post says cross-selling works well for “considered purchases”, the ones with higher cost and higher involvement. The consumer who uses simulations to evaluate products will almost certainly be ones prepared for higher involvement in the procurement process (whether in B2B or B2C) — natural candidates for cross-sales (and the consumer will likely be appreciative of the relevance of related products or services).
- Again quoted from Mike Svatek’s webinar, the post says up-sells work best when there is “a small difference in dollar value or a small nominal percentage difference – 10-20% max. You need to show some incremental value for the increase in price.” Including optional product features in the simulation is a great way to lead consumers to the complete product they need.
Simulation as Resilient Job according to NY Times
I just came across an article from the New York Times entitled “In Simulation Work, the Demand is Real“. The article is from a feature about emerging job markets, and basically implies that there is a good demand for jobs in simulation. Great!
In general, the article is fairly innocuous but it leads one to believe that the interesting areas of simulation are about modeling more and more complex systems (for example, it quotes a scientist at AEgis Technologies as saying “we solved most of the problems that one person can do a long time ago”). I think it perpetuates the myth that simulation advances and benefits only are interesting for high-end, complex systems. I really believe that simulation of more mundane processes and equipment has a huge potential impact that is not being realized or accomplished today, because simulation is often assumed to be complex and expensive.
Furthermore, the article suggests that the validity of the science behind simulation is almost a given, it’s just computing power which is lagging. Again, a big simplification. All models have assumptions. I have seen firsthand how simulation developers will try to stick models together without understanding that the assumptions underlying the models may be inconsistent.
I don’t want to be too critical because I understand the article is about high-end simulation, but I would have liked to see a nod to more mainstream applications of simulation.
Recent activities in Fire
My current focus regarding equipment simulations is in the Fire Service. My company has created a few simulations for the leading magazine/publisher in the industry, Fire Engineering. I really enjoy working on equipment in this industry because you can see immediately how useful the hands-on aspect can help the firefighters learn to apply equipment properly. We’ve also developed a following for our team-based training platform, CommandSim. That program can integrate equipment usage, but to date it has been focused on training for strategy, tactics, and communication.
Fire Engineering has just started a social network for training in the Fire Service (click here), and this will give me some public exposure to present and discuss issues around simulation that really relate to a variety of industries.
Upcoming Appearances
