Why Technology Won’t Help You Understand Your Customers

Were you surprised to read the title of this post? Do you believe that using technology to understand customers is the only way today? Then let me explain why I believe it’s not quite that simple. 

In today’s data-rich environment I’m not really suggesting that you actually ignore data nor technology! However, in working with clients around the world as well as in numerous industries, I have found that many are lost by the wealth of information that is available to them.

In fact it seems to drown out their reasoning of what to do with all the data and they remain frozen in indecision. Or worse, they invest in the latest platforms and systems in the hope that using technology to understand customers will help them with their knowledge void. Is this your case? If so, then just follow the steps I detail below and you will soon be doubling, quadrupling, if not getting 10x the ROI from your data.

 

The Current Situation with Data

Data is everywhere and most organisations are drowning in it! Technology is being blamed for disrupting businesses, but in most cases these companies have simply not adapted to this new data-rich world.

If you're drowning in data, perhaps you have still not adapted to today's data-rich world. #BigData #Analysis #Customer #CustomerUnderstanding Click To Tweet

I admit, a lot has changed. Consumers are adapting their behaviours to the trading of their personal information. Companies are changing business models as their value shifts from products to services, or even to the sale of the information they gather.

Some organisations are reinventing themselves to take advantage of these changes. Others are ignoring them – at their peril – since they are at risk of becoming the next Kodak, Borders or Blockbusters. And of course the latest covid-19 epidemic will hasten many others to unfortunately follow suit in the coming months.

If you’re interested in reading an analysis of the US Retail Apocalypse and the 23 big retailers closing stores then I highly recommend this post on Fox Business from last year. No doubt it will need updating in 2021 when the fallout from the current pandemic becomes clearer.

So what should you do? Well, I believe that you should start by renovating your business model to take advantage of the countless new opportunities all the data and new technologies open up for you. And in my opinion, you had better do it sooner rather than later, because your competition will almost certainly be investigating ways to make use of it all!

 

The Opportunity

Yes you have data and information, but if you’re a regular reader of my blog, you will know that you have to turn these into knowledge to understand your customers. And then develop insights and actions. But this can only be done by asking the right questions of your data and information. The latest technology is not going to make up for your lack of thinking!

If you are struggling to take needed action despite a wealth of information, then this is certainly where you should start making changes – fast!

A 2015 Capgemini and EMC study called “Big & Fast Data: The rise of Insight-Driven Business” showed that:

  • 56% of the 1,000 senior decision makers surveyed claim that their investment in big data over the next three years will exceed past investment in information management.
  • 65% admit they risk becoming irrelevant and uncompetitive if they do not leverage data. This is especially true given that non-traditional providers, like startups thriving on big data processing, are moving into their industries.
  • Although companies realize they desperately need to dig into data analytics to maintain their business position, 45% surveyed think their current internal IT development cycles are not sufficient for new analytics and don’t fulfill their business requirements.
  • Making matters worse, over half (52%) of those surveyed see the speed of their organization’s insight generation from data analytics as constrained by its existing IT infrastructure.
According to @Capegemini, 65% of executives admit they risk becoming irrelevant & uncompetitive if they don't leverage data. This is especially true given that non-traditional providers, like startups thriving on big data processing,… Click To Tweet

So what has happened in the past couple of years? Not a lot in terms of usage, but a lot in terms of data gathering; just check out the graph below from Kleiner Perkins for current and estimated growth of data volume. It is expected to more than triple over the coming five years.

 

 

Of course big data has been big news for years, thanks to its 5Vs (volume, velocity, variety, variability, value). These were the driving forces behind the need and finally the upgrades in computing power that made it possible to adopt a new and significantly faster way of analysing it all.

This article by Olivia Ryan sums up the “6 ways big data expansion can significantly damage our privacy.” These are the same major points that the GDPR hoped to address.

The EU’s GDPR (General Data Protection Regulation), with its stricter rules that came into force last year, focuses on many of the data privacy issues that have people the most concerned. It is definitely worth checking out the details here if you have still not made the necessary changes within your own organisation.

Interestingly, there is no equivalent federal law in the US (for now), but that doesn’t mean you can ignore it if your business is based there. Find out more in this other excellent article on Forbes.

It’s true that companies do recognise all the threats detailed in the earlier mentioned study, and while startups flourish in every industry, the mastodons of commerce are generally much slower to change, hence the need for GDPR. (see below for an alternative approach to individualised data utilisation)

 

An Alternative Approach

Data comes into its own when used for personalised engagements. However, there is an alternative or complementary approach that some organisations are now using. This is to address global issues such as resource management, water usage or pollution, which certain customers feel passionately about.

 

In Conclusion

Coming back to the title of this post, as you can see there is a lot to consider before using technology to analyse all the data you have. And probably it’s a lot more than you even know about at present, at least from my experience!

You can’t go wrong if you start with the customer and identify what you need to know and understand about them, in order to go beyond their expectations.

You can't go wrong if you start with the customer & identify what you need to know & understand about them. #CEX #CRM #Customer Click To Tweet

Make a list of all the things you want to know and then see if you have the information to answer them. In many cases you do, it just hasn’t been analysed in a way that makes the solution obvious. That’s when you should review and eventually update your platform and systems, not before.

Doing this any earlier will be like buying a fancy new hammer to crack a nut! What you need to understand is the best way to crack the nut; often times your current hammer is fine for cracking if you use it correctly.

 

If you’re drowning in data and thirsting for actionable insights, then we should talk. Click the button below and I’ll give you some ideas on how to crack your own nut!

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This post was first published in March 2018 and has been updated regularly to reflect the latest ideas, research and opinions.

 

 

You’ve Got Data? Well Don’t Start There!

Did the title about Data make you curious? Great!

Of course, in today’s data-rich environment I’m not really suggesting that you actually ignore it! However, in working with clients around the world and in numerous industries, I have found that many are lost by the wealth of information that is available to them.

In fact it seems to drown out their reasoning of what to do and they remain frozen in indecision. Is this your case? If so, then just follow the steps I detail below and you will soon be doubling, quadrupling, if not 10x the ROI of your data.

 

The Current Situation with Data

Data is everywhere and most organisations are drowning in it! Technology is being blamed for disrupting businesses, but most have simply not adapted to this new data-rich world.

I admit, a lot has changed. Consumers are adapting their behaviours to the trading of their personal information. Companies are changing business models as their value shifts from products to services, or even to the sale of the information they gather.

Some organisations are reinventing themselves to take advantage of these changes. Others are ignoring them – at their peril, since they are risking to become the next Kodak, Borders or Blockbusters. If you’re interested in reading more about the US Retail Apocalypse and the 23 big retailers closing stores then I highly recommend this post on Fox Business.

So what should you do, whether you are in manufacturing or retail? Well, I believe that you should start by renovating your business model to take advantage of the countless new opportunities open to you. And in my opinion, you had better do it sooner rather than later, because your competition almost certainly will!

 

The Opportunity

Yes you have data and information, but if you’re a regular reader of my blog, you will know that you have to turn these into knowledge and understanding, and then into actionable insights. And this can only be done by asking the right questions of your data and information.

If you are struggling to take needed action despite a wealth of information, then this is certainly where you should start making changes – fast!

A 2015 Capgemini and EMC study called “Big & Fast Data: The rise of Insight-Driven Business” showed that:

  • 56% of the 1,000 senior decision makers surveyed claim that their investment in big data over the next three years will exceed past investment in information management.
  • 65% admit they risk becoming irrelevant and uncompetitive if they do not leverage data. This is especially true given that non-traditional providers, like startups thriving on big data processing, are moving into their industries.
  • Although companies realize they desperately need to dig into data analytics to maintain their business position, 45% surveyed think their current internal IT development cycles are not sufficient for new analytics and don’t fulfill their business requirements.
  • Making matters worse, over half (52%) of those surveyed see the speed of their organization’s insight generation from data analytics as constrained by its existing IT infrastructure.

So what has happened in the past couple of years? Not a lot in terms of usage, but a lot in terms of data gathering; just check out the graph below from Kleiner Perkins for current and estimated growth of data volume.

 

Big data trends Kleiner Perkins 2017

Of course big data has been big news for years, thanks to its 5Vs (volume, velocity, variety, variability, value). These were the driving forces behind the need and finally the computing upgrades which made it possible to adopt a new way of analysing it all.

This article by Olivia Ryan sums up the “6 ways big data expansion can significantly damage our privacy.” These are the major points which the GDPR is hoping to address, and about time too in my opinion.

Today it’s the EU’s GDPR or General Data Protection Regulation, with its stricter rules coming into play later this year, which has everyone concerned. It is definitely worth checking out the details here if you are not sure what you need to change by when.

Interestingly, there is no equivalent federal law in the US (for now), but that doesn’t mean you can ignore it if your business is based there. Find out more in this excellent article on Forbes.

It’s true that companies do recognise all the threats detailed in the earlier mentioned study, and while startups flourish in every industry, the mastodons of commerce are slow to change, hence the need for GDPR. (see below for an alternative approach to individualised data utilisation)

 

An Alternative Approach

Data comes into its own when used for personalised engagements. However, there is an alternative or complementary approach that some organisations are now using. This is to address global issues such as resource management, water usage or pollution, which certain customers feel passionately about.

 

 

In Conclusion

Coming back to the title of this post, as you can see there is a lot to do before analysing all the data you have. And probably it’s a lot more than you even know about at present, at least from my experience!

You can’t go wrong if you start with the customer and identify what you need to know and understand in order to go beyond their expectations.

You can't go wrong if you start with the customer & identify what you need to know & understand. #CEX #CRM #Customer Click To Tweet

Make a list of all the things you want to know and then see if you have the information to answer them. In many cases you do, it just hasn’t been analysed in a way that makes the solution obvious. That’s when you should review and eventually update your platform and systems.

Doing this any earlier will be like buying a fancy new hammer to crack a nut! What you need to understand is the best way to crack the nut; often times the hammer is fine for cracking if you use it correctly.

 

If you’re drowning in data and thirsting for insights, then we should talk.

Contact me here: https://c3centricity.com/contact

and I’ll give you some ideas on how to crack your own nut!

 

 

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Market Research, Business Intelligence & Big Data: Have we Forgotten about Human Data?

The annual pilgrimage to the ESOMAR Conference took place last week in Dublin. I heard that there was much discussion, both on and off the stage, about Big Data and the future of market research. Hopefully, the whole profession will get behind one initiative, instead of each individually trying to “solve world peace” on their own!

This week sees the second Swiss BI-Day taking place in Geneva and there will no doubt be similar discussions about Big Data and the future of Business Intelligence.

It appears that Big Data is not just a buzzword or a commodity that has been likened to oil; it has become the centre of a power struggle between different industries. Many professionals seem to be vying for the right to call themselves “THE Big Data experts”.

This got me thinking about the future of data analysis in general and the business usage of Big Data more specifically. There seems to be no stopping the inflow of information into organisations these days, whether gathered through market research, which is proportionally becoming smaller by the day, or from the smartphones, wearables and RFID chips, that get added to every conceivable article, more generally referred to as the IoT (Internet of Things). Who will, and how are we to better manage it all? That is the question that needs answering – soon! (>>Tweet this<<)

Data Science Central published an interesting article earlier this year called “The Awesome Ways Big Data Is Used Today To Change Our World”. Already being a few months old probably makes it a little out-of-date, in this fast changing world we live in, but I think it still makes fascinating reading. It summarises ten ways that data is being used:

  1. Underst anding and Targeting Customers
  2. Underst anding and Optimizing Business Processes
  3. Personal Quantification and Performance Optimization
  4. Improving Healthcare and Public Health
  5. Improving Sports Performance
  6. Improving Science and Research
  7. Optimizing Machine and Device Performance
  8. Improving Security and Law Enforcement
  9. Improving and Optimizing Cities and Countries
  10. Financial Trading

Many of these are not new in terms of data usage nor business analysis. What is new, is that the data analysis is mostly becoming automated and in real-time. In addition, the first and second items, which were largely the domains of market research and business intelligence, are now moving more into the h ands of IT and the data scientists. Is this a good or bad thing?

Another article posted on Data Informed a few months after the above one, talks about The 5 Scariest Ways Big Data is Used Today   and succinctly summarises some of the dynamic uses of data today. The author of both pieces, Bernard Marr, wrote that “This isn’t all the stuff of science fiction or futurism. Because the technology for big data is advancing so rapidly, rules, regulations, and best practices can’t keep up.” He gives five examples of where data analysis raises certain ethical questions:

  1. Predictive policing. In February 2014, the Chicago Police Department sent uniformed officers to make “ custom notification visits to individuals whom they had identified, using a computer generated list, as likely to commit a crime in the future. Just one step towards the “Minority Report”?
  2. Hiring algorithms. Companies are using computerized learning systems to filter and hire job applicants. For example, some of these algorithms have found that, statistically, people with shorter commutes are more likely to stay in a job longer, so the application asks, “How long is your commute?” Statistically, these considerations may be accurate, but are they fair?
  3. Marketers target vulnerable individuals. Data brokers have begun selling reports that specifically highlight and target financially vulnerable individuals. For example, a data broker might provide a report on retirees with little or no savings to a company providing reverse mortgages, high-cost loans, or other financially risky products. Would we want our own families targeted in this way?
  4. Driving analysis devices may put you in the wrong insurance category. Since 2011, car insurance companies like Progressive and Axa, have offered a small device you can install in your car to analyze your driving habits and hopefully get you a better rate. But some of the criteria for these lower rates are inherently discriminatory. For example, insurance companies like drivers who stay off the roads late at night and don’t spend much time in their cars, but poorer people are more likely to work the late shift and to have longer commutes to work — both of which would be strikes against them when it comes to calculating their auto insurance rates.
  5. Walmart and Target determine your life insurance rates. OK, not directly, but Deloitte has developed an algorithm, based on “non-traditional third-party sources” that can predict your life expectancy from your buying habits. They claim that they can accurately predict if people have any one of 17 diseases, including diabetes, tobacco-related cancer, cardiovascular disease, and depression, by analyzing their buying habits.

Marr starts this article by very briefly discussing privacy and inherent biases in data. I think these issues are far more urgent than deciding whether it is market research, business intelligence or data scientists that are in charge of the actual data analysis. Perhaps we all need to work together so that the “Human” side of data is not forgotten? After all, most data comes from people, is understood – if no longer strictly analysed – by people, for the benefit of people, to help change people’s behaviour. What do you think? Join the conversation and let your voice be heard. (I’ll be presenting this very topic at the Swiss BI-Day this coming Tuesday, so I do hope that you will pop by and listen)

Winning Customer Centricity BookThis post includes concepts and images from Denyse’s book  Winning Customer Centricity. You can buy it in Hardback, Paperback or EBook format in the members area, where you will also find downloadable templates and usually a discount code too.

The book is also available on Amazon, Barnes and Noble, iBook and in all good bookstores. If you prefer an Audiobook version, or even integrated with Kindle using Amazon’s new Whispersync service, it’s coming soon!

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