In recent times, the need for b2b demand generation reporting, valuating organization and structuring of operations has gone up. Not just this, delivering what has been said to a best practice has become a challenge in itself. This is happening because of some strategic shifts in consumer behavior. According to BrightLocal’s Local Consumer Review Survey, 79% online shoppers trust online reviews.
Also, over 70% of the people surveyed admitted that these online reviews have a positive effect on their buying habits.
Today, people trust the opinions of their family, friends, colleagues and random strangers they might talk to than the marketing or the word of brands.
Another important statistic to consider is how people are always online in the latter part of this decade. According to Pew Research Center, 87% of mobile users are engrossed in their mobile phones while watching television. Today’s population is always online and always social. According to the same research, out of twenty-four, 2.7 hours each day are spent by US citizens online, and half of this time is spent on social networks. These are consumer habits which every operation must align to and accommodate itself to because they are widespread and changing the game.
In light of this, following are four pillars of B2B demand generation:
1. Business, brand and marketing strategies
The foundation of this pillar is based on a competitive advantage. This advantage should be compelling. The nature of business, brand and marketing strategies is that it includes planning and implementation. It also includes closed loop demand center operational structure. This pillar is based upon consistency, and with the Demand Center at its hub, an ROI-centric culture promotes excellence. The assumption taken in any b2b demand generation is that the market has a need which has not been met as of yet.
2. Technology: big data and marketing operations enablement
This pillar is powered on the basis of data insights and data access of the differentiated consumer experiences, as collated by integrated technology. There is a lot of data available. Which data is useful in drawing conclusions? This pillar involves building a data strategy to determine precisely this.