Month: April 2014

 

Winning With New Products; A Theory of Normalcy

Originally published in The Huffington Post on 02 April 2014.

Fact: The more we understand about the lives and environment of our target customers the better we are able to market our products to them and accelerate adoption.

Focusing on the use of technology by a market and their “Normal” level of technology sophistication can provide significant insight into the likelihood of that market’s adoption of new technology products and services, allowing firms and stakeholders to better define their target market and to refine their product offering for greater customer take-up.

Markets are complex and fascinating. Understanding how they work and how they pertain to and define your product or service are critical to the success of your business. “Will customers buy my product/service?” “Why will they buy?” The concept of “adding value” is core to any business case.

Generally and particularly so in the tech industry, your peer group – the guys you hang out with in Tech City, the guys you sit next to in your shared workspace – are not the right benchmark for your product to succeed. They are not representative of the mass market. If they think your idea is great and they are likely to use it, you really really need to double check whether less tech orientated consumers will adopt your product. There are early adopters but there are also too-early adopters. Niche products proliferate amongst tech folk, many of which will never get to the mainstream. There is a “market perception bias” due to peer group and the pressure to deliver cool innovation relative to localised behaviour. The product/service misses the mass market as it is too cutting edge.

Normalcy cartoon

The Adoption Curve

Most people are familiar with the Adoption Curve (The Bass Diffusion Model to give it its proper name – find out more on Wikipedia) that describes the penetration of a new product in a population. Be it subconsciously, it defines our forecasts when launching new products and, by inference, investment decision-making and capital allocation.

An issue with the model: keeping all parameters constant while varying the size of the market, the length of time to fulfil 100% market potential is always the same.

Estimates of the key parameters are made on existing sales data or synonymous comparables data. The size of the market variable is arbitrary – there is no prescribed science behind it. You can make it 1000 or 100 million and the key output, the estimate of customers, do not change except in scale relative to the initial input.

I hope you agree, this does not make sense. A firm launches a product, it is selling well. They then incorrectly assume that their existing customers are a sub-set of a very large market and build marketing strategy and estimates on sales revenue on this misplaced market definition. It will take them forever to “own” the market; it cannot be that the length of time to saturate a large, more heterogeneous market is the same as a small and more appropriate one.

Market segments are defined by habits and behaviours as well as in many cases, law. They are not defined by demography – age, location, density….though, in certain cases, demographics may act as a good proxy.

Banks don’t sell mortgages to the “UK market” they sell mortgages to people in the UK that are looking to buy property, a need driven by the behaviours the people within that group and in this example, the laws that apply, which further segments the broad market; commercial mortgages, investment mortgages, first-time buyers, etc. More granular still, individual mortgage “products” are defined to appeal to specific customer groups that are driven by even more granular behaviour; e.g. their level of risk aversion, their accumulation of wealth, their use of time.

Broadly (and maybe controversially?) speaking, I believe it is good practice for young businesses or for any business launching a new product to focus on a very small market segment, really understand it, own it, then broaden the market definition and leverage their experience and brand credibility from previous success to sell to new target customers.

Understanding your customer’s normal level of technology use is key to marketing and success

First, lets get everyone on the same page with a couple of definitions:

“Technology”, does not just relate to computers or electronics. It is more broadly defined as “The application of scientific knowledge for practical purposes” this could relate to machinery, pipes, a saucepan and even a comb.

“Innovation, is not just invention, is not just a new product or service, I define it broadly as “something new that adds value”. This could relate to a process, a product or service, a business model.

Combining the two, “technology innovation”, therefore is the application of scientific knowledge to create something new that adds value.

Lets say there is an arbitrary line that represents the technology innovation that is available to us. The further along the line the more “high-tech” the product and service. We can benchmark a “Normal” (mean) for the sophistication of technology people within homogeneous groups are comfortable using on a regular basis. Either side of this Normal, is a range that represents the inferior and new technology that we are willing to utilise today. For a very large market definition, this is, unsurprisingly, normally distributed.

base model

As time goes on and users accept and use more innovative technology, the normal shifts to the right, i.e. the normal level is at a level of more sophisticated technology tomorrow than it is today. This is usually an incremental transition and takes time. There are very few “disruptive” products or services that have led to a large shift in the normal level of technology utilised by a market. “New and Improved” trumps disruption every time. To ensure you acquire rapid acceptance and use of your service or product, you need to target somewhere to the right of the normal line. Excellent – all fits well with the adoption model.

But wait, we know there are more distinct groupings within the population. What if we were to consider the habits and behaviours of “technophiles” and “technophobes” as exogenous to the mass market?

To generalise, technophiles are more likely to adopt new technology innovations and will be less accepting of inferior technology, while technophobes are less likely to adopt, relative to the mass market. The chart is likely to look like this, with technophile and technophobe adoption of technology skewed appropriately.

decomposed

Now let’s make this more useful; let’s multiply the y-axis by the size of each market segment to give us a representation of the number of consumers likely to use the product:

decomposed2

Where do you want your product to sit?

To me, it’s fairly obvious that, for a product to be successful in the mass market, a business should be targeting the technology sophistication of the product to be slightly inferior to the normal level of technology sophistication acceptable to a market of technophiles. I.e. if the guy sitting next to you in google campus or a.n. other tech workspace thinks your product is cool and innovative (for them), it should ring an alarm bell in your head – check, re-check, and check again what is normal for your mass market.

Banks Must Catch the Innovation Bug

Originally published in The Huffington Post on 5th March 2014.

Although I agree that Banks and Financial technology firms should be looking to partner and work together where possible to improve the proposition for customers, I don’t necessarily believe that this strategy will make banks more innovative and provide better services for you, I and our businesses.

As I have stated before, innovation occurs at 4 levels correlated with increasing returns for the business and customers:

  1. Process
  2. Product/Service
  3. Business Model
  4. Industry – changing the way participants compete

My experience in financial services is that banks are pretty good at Level 1 – by buying in tech to improve process – and not too bad at Level 2 in certain areas.

Just look at the advances in process and products around capital markets such as electronic trading, algorithmic trading and prime brokerage. They are pushed to be innovative in these areas as the buyers, other financial institutions, hedge funds, etc. have significant power.

Downstream, in commercial and retail banking, there is less evidence of innovation in practice; chip and pin was a startling improvement that put the UK ahead of most other countries, but then we look at areas such as international payments, where the correspondent banking system from the 70’s is still in place, or invoice finance, where I have personally seen green screen terminals in a bank that run core processes.

It is still far too common that banks, rooted in tradition, try and keep the benefits of innovation for themselves rather than sharing with the customer equitably. This has to change; when it does, it will be the foundation of a new evolved industry.

For banks to become more innovative requires them to adopt a change in approach (be it slow and adaptive) to the way they do things, to the way they frame their role as a service provider, to they way they define and then execute their strategy.

This change requires buy-in from the top, from the board. It will take time and needs to be planned and controlled to fit with the bank’s culture and to avoid widespread disruption. Openness and collaboration with the rest of the bank is key; not just for others to see the benefits in the new approach, but to be inclusive and create a stakeholding. Segregating the (innovation) team is the biggest mistake that can be made – it will stir resentment that will lead to failure.

The CEO of one of the larger European banks I have worked with put it to me quite eloquently,

“Our business is like a large oil tanker, it takes a lot of effort to make it change course. What we need are a few agile speedboats that buzz around the tanker. Eventually, as more speedboats catch the tanker, the wake of these boats will help make the tanker turn more easily.”

We have not really seen a major bank challenge the industry with innovation at Level 3 and 4. Saxo Bank and Well Fargo are recent examples of business model innovation, but it has not called the larger players to account.

I am certain that, as has occurred in other industries over the past 20 years, a new entrant or existing player will grasp the reigns of innovation, be it organically, or, more likely, acquiring capability through external talent, so wholeheartedly that it fundamentally changes the way the industry competes – Level 4. This is where real value is delivered to all – Apple (Music industry), Ryan Air (airlines), Skype (communications). We are on the verge. I am so excited to be involved in the new dawn of financial services.