Product selector and sales tool

September 25, 2008

I’ve just posted a new version of the TouchConvert Interactive sales tool on my main site. Check it out and let me know what you think. This builds on an earlier posting on Product Benchmarking.

Launch the interactive version of TouchConvertTM



Intuitive Bass Diffusion

July 4, 2008

There is an excellent post by Mathias, which rephrases the Bass diffusion curve in more accessible terms and language. You can view his posting for the full explanation. I’ve taken the Excel file and created an interactive dashboard from it.

Click here to launch the Dashboard


Interactive Gompertz Model

June 28, 2008

In high tech start-ups the development cycle can last for a period of several years. We can capture new product introduction where the pre-revenue start-up phase is anticipated to be long using a Gompertz curve. There is a full description on Wikipedia.

Sales Function


Cumulative Sales Function


m

500

Ultimate market potential (m)

b

0.4

Scale Parameter (b)

η

30

Shape Parameter (n)

Click here to launch Interactive Gompertz Model


The Xcelcius dashboard allows users to interactively vary the parameters of the model. This is useful when doing ‘what if’ analysis during product portfolio planning stage. The sales profile is more realistic and can be embedded into the interactive portfolio or we can create a Monte Carlo income statement with distributions to describe uncertainty.


Index of Interactive Dashboards

June 25, 2008

Interactive Portfolio Model – Posting / Dashboard

Product Requirements Capture and Competitive Benchmarking – Posting / Dashboard

Economic Value Model – Posting / Dashboard

Bass Diffusion Model – Posting / Dashboard

Value at Risk – Posting / Dashboard

Net Present Value – Posting / Dashboard

Gompertz Model – Posting / Dashboard

Intuitive Bass Diffusion – Posting / Dashboard

 


Interactive Bass Diffusion Model

June 25, 2008

Click here to launch Interactive Bass Diffusion Model

The Bass diffusion model was developed by Frank Bass and describes the process how new products get adopted as an interaction between users and potential users. The model is widely used in forecasting, especially product forecasting and technology forecasting. Click here for the full description on Wikipedia.

The function describing Sales S(t) is given by


m

500

Ultimate market potential

p

0.02

Coefficient of imitation

q

0.4

Coefficient of innovation

Click here to launch Interactive Bass Diffusion Model

The Xcelcius dashboard allows users to interactively vary the parameters of the diffusion model. This is useful when doing ‘what if’ analysis during product portfolio planning stage. The sales profile is more realistic and can be embedded into the interactive portfolio or we can create a Monte Carlo income statement with distributions to describe uncertainty in ultimate market potential (m), coefficient of imitation (p) and coefficient of innovation (q).



Market Requirement and Product Fit

June 25, 2008

In a high value technology product there are typical three types of stakeholder that have separate concerns who each ‘speak a different language’. These types of buyer are highlighted in Crossing the Chasm. The economic buyer, technical buyer and user.

When building a sales proposition and message it is common to make the mistake of trying to force your perception of benefits, which may not be shared by your customer. It is also easy to convolve messages, which may not be relevant to the buyer you are talking to, for example, focusing on price or ROI with a technical buyer.

We want to deliberately and separately address the concerns of the technical buyer and the economic buyer. We can use an interactive dashboard to capture market requirements and support the sales process from the technical buyer perspective.

Product Requirements Capture and Competitive Benchmarking – Click here to launch the product dashboard

Instead of pitching a solution to a perceived problem we can work with a technical buyer to capture their ‘total’ requirement and the key points of pain. The feature or performance space has many dimensions, for example, size, weight, speed etc. Different requirements will also have different levels of importance, some are essential and some are ‘nice to haves’. With the dashboard the technical buyer can work though the feature list and select their target requirement and associated importance. They build up a map of the total requirement, which is then plotted on a spider diagram. They can drill down in a gap analysis chart to compare specific features across multiple products.


Target real needs in sales process – Instead of ranting about ‘guessed’ requirements, you allow the customer to fully articulate their need. There will be fewer objections as you spend more time understanding the problem instead of pitching a boxed solution. As they work through the requirements and weighting you can engage them to better understand the reasoning and problem implications. For example, if speed is an essential requirement you may drill down to find that the implication of delay is under utilisation of another costly resource etc. This implication knowledge will be valuable in future sales where there are common problem sets.

Map the need to your product – There is no algorithm for sales! However if the customer builds up the map of total requirement and there is a good match with your product this can be compelling when making the decision. In addition the document is permanent; often you can bounce between objections on specific features, with this representation you keep a global focus. The technical buyer can forward this dashboard to colleagues and they will have an audit trail of the decision process.

Competitive Benchmarking – once the requirement has been mapped you can compare it not only to your own offering but also competitive products. Ideally you are demonstrating significant and compelling differentiation. Even if other products are comparable in meeting the requirement you are acting more in the role of an honest information broker as opposed to just hawking goods by saying anything. This may be valuable in building trust in the customer relationship, which is often a larger determining factor in the sales process.

Interactive and Engaging – Most people have sat through interminable power point pitches. The dashboard changes the process from a passive information dump to an interactive conversation. Also dashboards are new and different; people find them fun and ‘every little helps’ when you are trying to get the product and company noticed in the crowd.

Market Analysis – In addition to using a dashboard in a sales context they can also be used when doing market analysis. They are a lot more interesting than a questionnaire. I’ve previously described two principle uncertainties in new product introduction 1)’Likelihood of market entry’– a binary event; whether we can enter the market at all with a product and subsequently 2) ‘Market penetration and growth rate’ –the income over time for a product. The risks can be split into further levels of granularity. The requirements capture can be used to make a detailed assessment of likelihood of market entry. If your product has a very poor fit with requirement then the ability to enter the market at all is greatly diminished. For example if the ‘fit metric’ was 20% we could use this directly in our Monte Carlo portfolio analysis as the threshold for market entry. You can also spot requirement trends that can have a strong influence on the direction of your technology roadmap.

Interactive Economic Value Models – Click here to launch the value model

The language of an economic buyer is very different from a technical buyer. They use words like, cost savings, ROI, payback period, utilisation, efficiency, payment terms etc. Again we often fall into the trap of guessing points of pain instead of listening to the customer who actually feels them. We can use interactive dashboards to capture costs and metrics on the fly and automatically calculate saving, ROI etc.

We don’t talk about technical advantages at this stage; we assume we have addressed the needs of technical buyer at the level of requirements capture and we are now speaking to the person who writes the cheques (in reality we probably speak to both in a parallel fashion).


The example value model above was developed for the Lonestar chemical process monitor. A factory processing an arbitrary number of samples will have a proportion of faulty goods. If these are not detected then the faulty goods can be shipped to customers. The question is whether we can save money by employing a detection system to identify the out of spec goods. The user can input the number of samples they process and how many defects occur. They can then input the associated costs, for example if a batch of out of spec goods was shipped then there may be a direct monetary cost in refunding / paying compensation as well as potential for significant brand damage. If there are false alarms then we may end up scraping product which was actually good. The model takes these inputs and calculates the cost of not using detection vs the cost of using a detection system. They get metrics including ROI and payback period.