“Know thy customer” is the first commandment of business, for good reason. A company without a customer base is like a preacher without a congregation: at best, mislabeled. At worst, useless.
But an edict from on high does not a business strategy make. The natural follow-up question is of course: How do you know what your customer wants? And much more importantly: What are they willing to pay for it? In this age of e-commerce and the constant flow of information, big data may be the best answer to both questions.
This idea was pondered in a recent presentation by a Berkeley Teaching Fellow who speaks regularly at Silicon Valley Innovation Center. His presentation, part of a Leading Digital Transformation (LDT) program at SVIC, examined the impact of new technology in understanding customers and pricing dynamically to match their individual needs. Drawing on his wealth of experience and a series of case studies, our speaker showed that innovative companies are leveraging scores of data to segment their customers, continuously optimize prices, and increase revenue — all without ever changing a thing about their products or services.
Pulling the levers of profitability
The factors that determine profit are the same across every industry, from the biggest retail giant to the leanest software startup: production costs, product differentiation, competition, the timeless dance of supply and demand. Not least among these levers of profitability is pricing. By tweaking the variables in creative ways — cutting costs here, acquiring a competitor there — a company strives to max out its bottom line.
But optimizing these profit factors is no easy feat, especially when it comes to pricing. What one customer is willing to pay might be very different from another, and so a business must make some sacrifice to sell to them both at the same price (that is to say, one of those customers would have happily paid more). As before, this disparity between customers’ ideal price points is a burden shared by all industries. But in addressing this burden, those lean software startups — who have direct, personal, and unprecedented access to their customers — may have a leg up.
A traditional business practices price discrimination in traditional ways: sales, volume discounts, and loyalty programs (to name a few) are all ways to capture a broader customer base across multiple price points. A company like Groupon, which launched in 2008 as a “group coupon” platform, exemplifies this approach. By letting local businesses post discounts that would apply only if enough people bought in — a volume discount leveraged by the collective bargaining power of strangers — Groupon was one of the first companies to recognize technology’s potential for variable pricing. Today, the company goes far beyond group coupons: among other offerings, they use advanced AI to “power supply-demand matching” on an individual level.
Which brings us to:
(read more on https://siliconvalley.center/blog/know-thy-customer-how-big-tech-drives-profits-with-data-and-dynamic-pricing)