Ben Abraham, Co-founder & Head of Product and Innovation at IQBlade, shares his thoughts on the power of data.

Firstly, I have a confession to make. I’m a bit of a data geek. I’ve always loved the power of data to help make more informed decisions and solve problems. From using basic formulae in an Excel spreadsheet, to the large-scale processing of data algorithms to drive a machine learning process, there is a huge spectrum of complexity and relative accessibility.

From schoolchildren making a basic spreadsheet of temperatures and rainfall over time, taking averages for a basic future prediction; to Financial Services companies processing millions of data-points in real-time to calculate the potential risk of an applicant so they can choose to bid or not bid for the price comparison request in near-time; there is a dataset for everyone to use and learn from.

 

B2C is Ahead of B2B

We’re in the era of data. Many retail organisations have a deeper understanding of each of our preferences and biases than we do ourselves. They know when to combine complementary products into an offer, re-engage the disenfranchised shopper, and promote a new product line to those with the greatest propensity to purchase it.

Platforms such as eBay, Amazon and Alibaba have connected suppliers and buyers of many product lines and have data at the very heart of their operation. Financial Services companies are now able to query in real-time the credit and risk rating of a potential client to ensure they understand the market value (and potential cost) of doing business with them, and make an offer they hope is of representative value (or not, if the risks are too high).

Whilst data is central to many of the most successful growth strategies in consumer (B2C) markets, there has been a slower adoption of a data-centric approach in business-to-business (B2B) markets.

Why B2B Takes Second Place

A consumer is relatively easy to track (and classify) digitally. We all tend to have data which an organisation can link together (email; social media; personal credit card information; demographic profiling, etc.,) and, whilst I won’t touch on the wide subject of ethics in processing personal data and privacy in this blog, many of us are prepared to compromise by sharing certain elements of our digital lives for a more relevant, personalised experience online.

The Application of Consumer Data

It’s easier to manage data in a consumer sense as many of our personal attributes are readily classified and, therefore, it’s much easier to group segments of a consumer client base.

A business could take the social profile pictures of a group of customers and segment those with beards aged 30-55, living in postcodes which suggest they are a relatively high net-earner. That business could then offer a promotion to those who have not yet bought a high-end shaving kit and offer retargeted adverts on various social media advertising platforms.

It is also relatively easy to quantify the cost of marketing to an individual and then track their purchase history to ensure that the return on investment (ROI) is optimised. For example, the company can see they spend on average £1.99 advertising to each prospect, convert 5% of those with a sale, and calculate the lifetime value of an average client to that brand at £149. So, for every £39.80 spent on advertising, that company will generate £149 over the lifetime of that client. A good and repeatable business model which could be further optimised through testing conversion rates on different advertising platforms for sub-segments of that group.

The B2B Challenge

The challenge in driving data in a B2B setting is that there may be tens of thousands of employees, and we might not know the decision-making process of that company.

  • Who is going to make and/or influence the buying decisions?
  • In which region will those decision be made?
  • How do we find the relevant employees in that business to market to them?
  • Which companies do we want to sell to?
  • What does a good company look like for our product or service?

It is a much more involved process to define the relevant attributes of an interesting prospective company, and even harder to identify people linked to that company’s decision-making process.

Companies are transforming many industries by building new business models which put data at the heart of their Go-To-Market. They recognise the huge commercial opportunity for organisations which better understand their own (and their competitors) customer base.

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