Having worked as a roadmap strategist for high tech companies for many years, I can state with confidence that many products that will be delivered to market in 10 years time are not possible to build today, based on todays technical know-how. I also feel confident in stating that the market is almost spurning a new generation every 5-7 years. So it is very likely that something that was tried 10 years ago will work very well today. But not to dwell on trying to rationalize my marketing strategy [incidentally, the same business tried my idea a few years following and it was a huge success!!].

The point of my post is that we can fall prey to chasing the same big whale, and not notice that the other pools of profit that were not apparent at the time we first entered a market have now become whales in their own right – right under our noses. I urge you to do a blanket analysis across the market on a regular basis, preferably by an independent third party source unbiased by the businesses current focus.

This video shares the experiences with Dan Siroker, previously of Google, then head of the New Media Analytics team for the Obama Campaign. Dan describes how the campaign used data to win the presidential election and shares the lessons his team learned along the way. One can apply these lessons to any data-driven decision one needs to make — whether it be in developing, designing, or even marketing.

Evidence, facts, science and feedback and how it was used interactively in the Obama campaign. Learn the top 5 lessons that should define the methodology of any new media campaign.

The five key lessons were:

1. Define quantifiable success metrics
2. Focus on your weakest links
3. Never over-generalize
4. Take advantage of circumstances
5. Question assumptions

Selling will always involve emotion – even to the most rational, hard headed buyer. All prudent marketers are aware of the decision making profiles of their main market segments. Some buyers make decisions purely on emotions and never really apply any logic. Some buy on emotion, then attempt to rationalize their purchase afterwards with rationale to either support their purchase to others or overcome buyers remorse. And the rationale, intellectual will carefully analyze all the pros and cons, but will always be swayed by an element of emotion – more in terms of fear or ego, rather than pleasure. Businesss Intelligence should lead marketing efforts in terms of segmentation and knowing your customers, then emotion comes into play in carefully crafting advertising copy to entice the desired response.

There is always a role for good judgement in business, even outside the hard data.

1. The basis for forecasting
2. The confusion between demand and targets

Many product based companies tend to forecast based solely on SKU. The true demand for any product or service is for the features that a product or service has. Each SKU needs to be regarded as a particular combination of features that define the product. The forecasts must therefore be based on combination of features and only then, linked back to SKU.

It is not uncommon to find many companies adopting the old ‘forecasting’ approach of 5% increase on the same month for last year, and add in any corrective factor for the current economy. This just doesn’t make sense. You may want to set your targets on this basis – if one of your corporate objectives is to increase sales volume by 5% over the whole product portfolio, but it is no way to forecast.

This raises the second fundamental error. Earnings targets are NOT forecasts. Forecasts are driven from the market up. Targets are driven from the boardroom down. They tend to collide in marketing with an alarming confusion of terminology. The demand from the market has nothing to do with the demand from your boardroom. Forecasts are demand planning, and it is hoped that the marketing tactics deployed generate sufficient demand to meet or exceed boardroom demand.