Digital Marketing - Which Analytical Insights Really Matter?

Digital Marketing Analytics is an important area for most companies at present as online channels become ever more influential in the marketing mix. Sometimes I get the impression that marketers are unnerved by the digital arena because it's challenging to build a robust performance management model.   In this series of articles sponsored by Adobe, marketers get to understand the key threads of knowledge they could, should or must invest in. It goes some way to demystify the digital marketing arena. Take a look...

Metrics That Matter

Using behavioral science to improve the customer experience | McKinsey & Company

This is an interesting article by McKinsey that highlights how business is now coming to terms with the need to register how customer structures and behaviors impact directly on operational excellence and performance.

Using behavioral science to improve the customer experience | McKinsey & Company: "e"

What Is Customer Science?

This week I've been putting together a presentation to introduce Customer Science and why I think it's now come of age thanks to Cloud CRM data-marts.

At one time, marketers like me really struggled to build a rich understanding of the customers in their target markets.  The first major challenge was to get customer data into a usable form.  With so many business systems designed to support a specific process or discipline, it's not uncommon for data to be held in many different back-office systems.  The Web made this situation even worse.  Even when marketers could get their customer database onto a spreadsheet (and you were lucky if it didn't blow up when attempting this due to the files sizes), data quality and inconsistency issues meant that marketers faced hours if not days of data crunching to get their data consistent.

In today's digital world a great deal has changed.  For one thing, the state of markets changes so quickly.  It would be a nonsence to try to attempt this type of 'single view' when customers ebb and flow on eCommerce websites on an hourly basis.  Another issue with digital customers is they don't interact using phones and face-to-face visits.  They don't want suppliers to call them out of the blue to ask them a hundred questions about their product interests, buying preferences, future plans or buying behavior.  We live in an era of event-driven, remote - practically always - online thoughtful consumers and buyers.  They're always on the look-out for a good deal, positive product or service recommendations, happy to snack online in pursuit of their purchasing interests - it's a very different world to the one Micheal Porter described in his marketing 'how to' articles.

In this presentation I've put down my thoughts on Customer Science and how it's rapidly maturing as a discipline.  I find the subject fascinating because, like many marketers, I share a huge interest in the fit between customer value and shareholder value.  I also have a belief that most customers are willing to buy your product or service if it addresses an unmet need - IF ONLY you can communicate to them in a fine-grained, relevant way.

I hope you enjoy this article.  Do let me have your feedback!

Ian.

What Is Customer Science - And Why Should You Care?

A Single View of Customer Data - Thanks Cloud ;-)

Sourcing a single view of customer data can be painful for marketers

In this article I take my first walk around using a BIG DATA private-cloud data-mart for marketing and comment on what it’s actually like as a marketer to be armed with a ‘single-version-of-the-truth’ when it comes to customer insights.

I’ve spent my career as a business-to-business marketer being (one of) the last to leave the office because THE NEXT marketing activity required data in a certain sort, form and quality that required me – and often my willing team – to stay behind and fix all of the wrinkles that fall out of exporting data from operational systems like Customer Relationship Management (CRM), Contact Management (CM) or Intranet repositories.

The marketing industry has spent a life-time grappling with poor quality data from operational systems and using it for a different purpose to what it was intended.  The vision of CRM and other systems was to create a ‘single-view-of-the-customer’.  Great.  Or at least it would be great if systems didn’t change, acquisitions didin’t happen and marketers only wanted to use data that exists within the organization. But this is the real-world, and in the real-world all of these factors impact on marketers to stretch their day.

Thankfully, the advent of cloud computing – and applications platform technologies like ENCANVAS – happily means that nowadays marketers don’t need to rely on operational systems to form their customer data-mart into a single view of the customer.  Private-cloud data-marts are a new form of technology solution to the age-old problem of how to create a nice, neat bundle of customer data that marketers can get their knife and fork into without first having to herd cats.

Sometimes falling under the all conquering umbrella of BIG DATA, CRM private cloud data-marts are a secondary layer of glue-ware:  Instead of creating a ‘new system’ and yet more data entry screens, CRM data marts harvest data from existing operational systems and website to build a holistic view of the customer and market landscapes.  Data is securely uploaded to the cloud using Business Process Management and Workflow tooling (in the case of Encanvas it’s called INFORMATION FLOW DESIGNER), and as it’s harvested, clever algorithms are applied to the data to correct all of those horrid things that marketers usually have to spend their time manually correcting in unwilling spreadsheets – missing postal codes, incorrect salutations, duplicate records, invalid email addresses and telephone numbers.  These algorithms cut a huge chunk of workload off of the marketers’ average day-job and can even cope when salespeople do ther inexplicable data entry faux pas like ‘dead@dontsendemail.com’.

Services like USTech Solutions’ Big Data Skunkworks mean that marketers are able to get up and running with their truly holistic view of customers remarkably quickly and start to show their metal by doing the great things that marketers joined the profession to do rather than the tedious data crunching stuff that drives them to distraction.

SO YOU WANTED A SINGLE VIEW OF YOUR CUSTOMERS – WELL NOW YOU”VE GOT ONE! SO WHAT CAN YOU DO WITH IT?

I’ve only been experiencing the impact of CRM data-marts through ENCANVAS deployments over the last few months and so (even though I’ve been waiting for 20-years to see the day!!). I’m only now getting my hands on the sort of data and tools that I dreamt of as a spotty marketing assistant back in the day.  The results I’ve experienced have so far been outstanding (I may well up!).  Using the interactive charting and mapping tools that are available now to marketers in CRM data-mart platforms it’s now possible to dive into views of data presented in charts or maps and see the related records below to see the detail. It’s also possible to click on the data that DOESN”T have an email, that DOESN’T have a scheduled reminder or scheduled follow-up – so action can be taken to act on what’s missing by resolving the poor working practice.  One can even filter the source of poor quality data to an original system, sales team or sales person!  There’s nowhere to hide for poor quality or incomplete data.

Having the ability to identify patterns and buyer behavior segments is proving extremely useful.  Having defined rules in the system of what constitutes a BAND A customer. or a BAND B customer, the platform will again manage these rules so that, any time a customer inherits these characteristics, they pop into the appropriate group.  Customer data can then be analyzed, sorted, formed into campaign lists (or whatever) by adding this additional ‘filter’.  From a practical perspective this means that marketers can be far more granular with their campaign straegies; they can select customers with or without certain data attributes, by band, by location, by date last contact, by income, by spend, by shopping behavior – gosh it’s fun!!!

Another factor that feels like it’s taking a load-off happens when I see poor quality data and I want to tackle it.  Instead of having to export ALL of the records that have no email address or no Cell/SMS number, I can now concentrate efforts on tackling the BAND A customers that have no email and make sure the most likely sources of business impact are handled first.  Very handy.

One thing I wasn’t expecting is that the data in the cloud data-mart is consistently good even when the data held in sourcing systems remains poor.  This is because the extraction tools that automate the population of the CRM data-mart cloud will install sorting, de-duping, cleansing and enriching treatments not just once but everytime a data upload takes place.  This means that if you’ve instructed the platform to look through your emails and kill any non-conforming data, it does so every time the source data is uploaded – so the result is the cloud always stays PURE.

Does this mean the world of the marketer has changed forever?  Not on a base level; the same old instincts, methods and skills apply. What is different is the IMPACT pragmatic marketing can make on business POWERED by private-cloud CRM data-marts.  It’s and accelerator to marketing innovation.  Of course it also saves me LOADS of time by not having to be knee deep in dodgy data which now allows me to go home at the same time as my sales colleagues that were probably the folk who put the poor quality data in the CRM database in the first place!! Thanks guys – I  forgive you (now).

Another big player in 'big data'

This article announces Goldmans' US$100m investment into big data analytics firm APT.   APT's description of its service is a dead-ringer for Data Investment Management and puts APT, WPP's Fabric (Fabricxx) and Encanvas on different parts of the same page.

Without question, harvesting data, analyzing it and acting on the things that matter is the hottest ticket in IT at the moment.  Whereas APT and Fabric are in the 'big corporate' market playing with big data, Encanvas serves the mid-market and harvests data from anywhere to build customer analytics.

Other notables in this space are Locationary, recently purchased by Apple, Teradata's Aster Data analytic platform, Dataspark in Australia and the people that started it all DunnHumby.

Disappointingly, a focus on the Big Data buzz is somewhat distracting as people seem to be confusing the world of Google, Facebook and Amazon dealing with HUGE DATA (let alone 'big') with the need by organizations to adopt Data Investment Management solutions that can discover data, analyze and act on it.

I.

What Are Actionable Insights?

I was delighted when so many sites picked up this simple presentation I've put together to describe what Actionable Insights are.

I think there is a great deal of confusion at the moment around the entire technology space because people are hearing whispers of BIG DATA, CLOUD, PREDICTIVE AND SOCIAL BUSINESS INTELLIGENCE and the like...  and what they really want to know is what any or all of these technologies have to do with their business.

For Business Intelligence Software vendors, it's not always easy to answer the 'So What?' questions when it comes to applying their technology; particularly when the people making the introductions are enthusiasts of technology - and they generally are.  If you are passionate about technology like me, you just want to shout out to everyone in the world "Hey, give this a try!" but every business, and business user has a different perspective on 'what insights matter most to them'.  Failing to appreciate and land on the specific insights useful to buyers and instead making a general technology silver-bullet pitch is an all too familiar Lion Pit that Business Intelligence vendors fall into.

This presentation covers descriptions of types of Business Intelligence software and the key outcome areas that are driving demand for Actionable Insights.  I've covered a lot of the background and technology issues in this presentation that I think are most helpful in understanding the general topic area. What I haven't done is to even start to describe the road-blocks and organizational design issues that are probably going to make the biggest difference to the value of Actionable Insights to early adopters of the technologies designed to source them.

These are about:

• Changing attitudes and behaviors.
• Appreciating that IT systems have focused for years inwardly on processes that exist WITHIN AND ACROSS the enterprise but rarely beyond it.  That means to really get to grips with harvesting and assimilating actionable insights new technologies need to be introduced along with new thinking on security governance, data governance, scaling and analysis tooling.
• Accepting that some Actionable Insights that are most valuable to an enterprise aren't being captured today at all (such as 'soft-measures').
• Some Actionable Insights don't have any specific role in the enterprise responsible and accountable for making use of them. 

I.

Operational Analytics: Best Software For Sourcing Actionable Insigh...

Operational Analytics: Best Software For Sourcing Actionable Insights:

In this article I summarize the buying options for businesses looking to source actionable insights - data views and reports that give managers cause to take action to improve the way they work and achieve double-loop learning results.

I hope you find it helpful!

Ian.

Talent Leaders Can Learn From Customer Science - To Foster 'Loyalty Beyond Reason'

 

'Loyalty' by Sherry Ezhuthachan

Stepping across from the world of marketing and brands into talent management has helped me to appreciate there are more common areas than I'd previously realized.  To be high achievers in the talent industry, HR and talent leaders will need to learn the lessons of brand managers.

...

"Loyalty Beyond Reason? - That's a funny name for a blog.."

I often get funny looks when I tell people about my new blog title.

I came across Loyalty Beyond Reason when reading one of my favourite books for the second or possible third time and I was reminded how central it is to running business in the noughties.  The book,written by Kevin Roberts, then CEO Worldwide of Saatchi and Saatchi, is called Lovemarks: The Future Beyond Brands.  It's a slightly annoying book because it's better than the three books on business I've written myself.  Anyway, reading the book you realize Kevin is one of those guys that 'understands' how customers and markets work at an 'organic' rather than 'theoretical' level, a bit like Richard Branson.

The key argument introduced in the book is that industry and commerce has moved from a focus on products, to (but products have become very similar, companies need to protect their IP some how and therefore we have..) trademarks, to (but customers don't connect to trademarks so we have..) brands to (but now we even have too many brands to think about so we need to give customers reasons to grow 'loyalty beyond reason' so we're heading towards..) 'Lovemarks'.

It isn't difficult for me to buy into the idea that companies don't own their brands anymore and - if they want their brands to be successful - they need their customers to take them on, buy into them, promote them.  Just look at brands like Apple and the passion users have for their products.  This isn't just a cold, calculating buying decision at work here.  Nope. These boys and girls LOVE their brand.  No matter how many advertising dollars go into Microsoft I don't see the same thing happening with that brand.  Now I know some of the guys at Microsoft in the product marketing teams and I have to say they're an exceptional bunch of folk.  They know their stuff when it comes to Outcome Driven Innovation and all the latest thinking and approaches on Product Management and how to deliver world class products.  Recent launches show there's nothing wrong with their products.  Yet they don't engender the same passion and loyalty in their customers as Apple has managed to do.  They are failing to create Loyalty Without Reason.

Spending my time in the talent industry over the past few months I've learned that the need for Loyalty Beyond Reason is missing in many employer:employee relationships, let alone contractor:contracted relationships.  The relationship between a customer and and a supplier very often only becomes contractual when the customer chooses their brand.  Before that they can go anywhere.  Perhaps employers think that because they have an employment contract in place they can within reason 'do what they like' when it comes to their relationship with staff and contractors - but this is a pipe dream.  Even when there are contracts and agreements, these don't create great productivity and game-changing ideas.  Like any contract, it's only really there for when the relationship breaks down.  No, if talent leaders want high performing workforce and world class talent, they're going to have to forget about contracts and compliance, using performance appraisals as a way of formalizing how the carrot and stick are applied, they're going to have to find better ways of creating loyalty beyond reason.

The brand industry knows that you can't tell customers to buy your products,  you can't even ask them nicely.  You have to get customers to want to buy.  And the buying decision isn't all about facts, analysis and reason, the last 9-yards is pure emotion; how it makes you feel to own a product or use a service.  I fly Virgin Atlantic because they play T-Rex when you walk down that long isle on the plane past the nouveau riche to economy. Makes me feel good.

Talent leaders need to invest in their people 'in a certain way' - not the Microsoft way, the Apple way.  As with the Customer Science industry, the starting point is to invest time in understanding 'the individual' and applying actionable insights to draw out the things people care about emotionally, on the edge of reason.  Any business can do this - big or small, accountants or engineers.  You just have to start in the right place.

I.  

Actionable Analytics Trends: 'Will Be Driven by Mobile, Social and Big Data' Says Gartner

Gartner Says Actionable Analytics Will Be Driven by Mobile, Social and Big Data Forces in 2013 and Beyond:

The Gartner article is interesting because it starts to evidence what most practitioners in the business intelligence field have I suspect known for some time - that instead of examining 'dead' data that has been purposely shaped, organized and crunched for the purpose of analyzing performance, we are heading into an era where the really useful 'So What?' type of analytical metrics will come from the live workspace environment.  Users of mobile phones, tablets, and PCs will contribute data unknowingly through their clicks and taps into the big data cloud while others will find their movements, preferences and locations picked up through sensors - on doors, on billboards, on product labels, on shopping trollies and vehicles.

Whilst this all sounds terribly 'big brother' to some generations, the techno savvy youth of today a leading a charge towards the 'thoughtful web' (as I describe it in my book 'Social Operating Systems') will think nothing of a few more sensors and clicks being monitored.  Most will have no choice if they want to afford to pay for motor insurance or use social networking sites like Facebook. You either agree to the supplier terms or are cast off.

Analytics is moving into the clouds to make this possible.  Platforms like Streaminsights from Microsoft and BusinessIntel from Encanvas enable data to be captured as it travels, or where it resides without needing to build data marts or purchase BI platforms.

It's going to be interesting to see how businesses adapt their thinking to take advantage of these new innovations and new ways of working.

I.

Benefits of Profiling Customers For Motor Dealers - And How To Do It

Customer Science - ...building deeper, richer, more personalized customer experiences by applying customer insights to better understand what customers care about, how they think and act, how they make buying decisions, how they want suppliers to communicate with them, how they want to be treated, what they expect from their suppliers... and more.  But does it work (is it working?) in  Motor Retail? Is it being used successfully to turn 'sleepy customer data' into a dynamo for new reasons to speak to customers, turning clicks and visits into cash?

...

Since the 1980's I've watched with interest as the methods adopted by marketers to engage customers and prospects have adapted as new technologies and created approaches have come of age.  More than in any era before, the noughties has required marketers to take on a cacophony of new techniques to engage customers that want the perfect mix of a personalized customer service experience and relevant, timely offers while not wanting to be barraged by suppliers with direct marketing and unwanted contact.  The growing impact of the Internet, mobile communications, social networking and a more techno savvy customer communities is changing the rules for marketers on how to get the biggest impact from their marketing spend.

By now, the marketing industry has worked out that it's vital to gather information on customers 'as part of the day job' to build up a profile and persona on each and every customer so the customer enjoys a personalized 'shopping' experience.  Companies like Tesco and Amazon have shown the way in exploiting customer data to sensitively give shoppers what they want rather than forcing them with a strong hand down paths they don't necessarily want to follow.

The type of relationship customers want - location-centric, timely, fine-grained, event-driven offers personalized to their particular wants and preferences - can only be achieved in my opinion by taking every opportunity to learn about customers through each and every interaction.  Customers don't want to be contacted out of the blue, or left standing in service receptions JUST SO THAT DEALER CAN CAPTURE DATA TO SELL TO THEM.  For Motor Dealerships that means not only investing time into collecting data 'as part of the day job' but also investing in the PROCESS of 'digital persona-lization'.

In an odd way, customers generally WANT suppliers to build and know their digital persona because they want that type of personalized experience (with the suppliers they want to buy from).  What they definitely DON'T WANT however are relationships with suppliers that abuse their trust or over-bite on the level of relationship they want.

Marketers in most industries profile their customers these days, but 'Customer Sciences' are only now appearing in the Motor Retail sector.  This is partly no doubt down to the fact that in certain countries and regions, dealerships with the right franchise have very little local competition for the brand they promote. While it's always silly to generalize, the feedback I get is that this is changing and levels of competition are growing in most geographies.

Understandably, dealer principles want to know:

• How does profiling help me to sell more?
• How do I build up profiles and personas from my data?
• How do I enrich my data when it's poor?
• How do I channel dialogue opportunities to encourage sales people to engage customers at the right time and for the right reasons?
• Where do I start?

So here I attempt to answer these questions:

How does profiling help me to sell more?
When dealers have a better idea of the sorts of customers they sell to they become more adept at appreciating the types of offers that work.  Knowing the affluence of customers on your database for example means that you can find out (from third party agencies like www.improvemydata.com) the addressable market in your locality by mapping these target customers against your existing database. Marketers and dealer execs can use the profiles they hold about their customers to understand how to maximize their revenue potential per customer - to then work out which customers are not achieving their anticipated life-time value. Sometimes enriching data can seem like a 'painting the Fourth Bridge'  experience where you need to start again every time you think you've finished.  Focusing on the most important customers first and devising marketing strategies to grow value in the customer segments that matter most allow marketers to drive optimal value from the smallest efforts.

How do I build up profiles and personas from my data?
There are many ways you can profile customers - the most obvious being:
(A) Life-time value - It's quite easy to derive a value for each customer based on assumptions of what they should spend over their lifetime.  Many motor manufacturers hold and share these insights for each model they sell.  Comparing your revenue per model against the forecasted return helps to qualify 'where things are going wrong or could be improved.  Seeing this data, dealerships can realize that some makes and models are more reliably generating the life-time revenues they should than others; perhaps because some makes and brands face more local aftersales competition than others.
(B Buyer behaviour - At NDMC we define the buyer behaviour of private vehicle buyers through fourn buying personas:

1.  Cherished Teddies > Loyal buyers that consistently reach within 20% of their future planned life-time value. Typically these customers will purchase service or loyalty plans (often with additional insurances or paint protection options) to make sure their dealership can look after their needs. For this group dealers should have a very complete picture of the customer profile.  Cherished Teddies need looking after because they are the group most likely to recommend others buy their vehicles from your dealership!
2. Loyal Dogs > Vehicle buyers that purchase after-sales products but don't achieve the future planned life-time value.  Understanding why this group doesn't achieve their future life-time spend is helpful because it can point to weaknesses in your offerings or aspects of local competition that you're not aware of.  At the same time, it pays to contrast buyer behaviour with affluence ratings given that it may well be that Loyal Dogs WANT to be Cherished Teddies - they just can't afford to be ;-)
3. Cats > Buyers that have purchased a vehicle from you but only come back for aftersales services when it suits them.  Just like cats you can't rely on their loyalty and you have to work harder to get their attention.  Cats are harder to love because they're not around as much. The obvious thought is 'What does it take to turn a Cat into a Loyal Dog?'
4. Neighbours' Cats > Buyers that haven't bought from your dealership but have bought services or parts. Perhaps these customers are 'sampling your dealership' to understand how well they get treated. If you pay them more attention, perhaps they will become your Cat in time.

(C) Affluence - How much money people earn is a good indication of how much disposable income they have to spend on a vehicle and indeed the sort of vehicle they might want to purchase.  Consumer data can tell you a great deal about who your current customers are and the target people in your area most likely to be willing and able to purchase a vehicle from you.
(D) Contact activity and preferences - It helps to understand these days 'HOW' customers want to communicate.  There is a significant shift to social media and mobile methods. Assumptions that 'mobile and Internet' tools are for the young are usually baseless. Many 'people that want to be young' are avid smartphone and Facebook users (My mum twitters all the time!).
(E) Location - Location awareness is a powerful market tool.  These days it's quite possible to focus events and campaigns to target specific geographies that have a proven bias towards your brand based on affluence or locality. Consumers can also be targeted 'on the hoof' if you have the means to engage them when mobile.
(F) Arbitrary Banding - Even when all of the above fail, marketers can start their entry into Customer Sciences by thinking about their own arbitrary bands based on a selection of customer metrics and see what falls out.  Dealer execs have a very good feel normally about their customers and what works and doesn't work.  Exploring these perceptions and seeing if the 'data' backs up the assumptions can be a good place to start for organizations that have never experimented with Customer Sciences before.

One other thought - unsurprisingly, when you compare these different aspects of profiling together it helps to build up a visual image of the 'persona' of the buyer and this can help to further develop the rapport with the customer through a 'deep support' understanding of their wants and needs.

Building up profiles is a question of understanding key data metrics and then validating where the data needs to be sourced from.  Sometimes data is already held in admin systems (like Dealer Management, Showroom or Service Management systems), while other times it will need to be captured by installing new systems or methods.  Not all methods require manual data entry.  These days, customers are often prepared to enter their own data provided there are rewards for doing so (such as gaining free access to an online portal that provides details on their vehicle valuation and the impact of their driving behaviour).

The life-cycle for Customer Science (i.e. creating and leveraging profiles) goes something like:
(1) Harvest - Gather and cleanse data from its various latent sources
(2) Make Connections - Build new connections between data items to produce new metrics
(3) Personalize - Apply the learning lessons to personalize the dialogue with customers and create new reasons to interaction with more relevant and timely offers
(4) Learn - Measure the effectiveness of personalized interactions and learn from them to source new ways of bringing value

Like most processes in business, the first job is to recognize that the process needs to exist and, having formalized it, it becomes something that can be measured and improved to become progressively more effective.

How do I enrich my data when it's poor?
In the motor dealership arena, the most frequent response I encounter is 'Sounds great but my customer data quality is so poor it wouldn't work for us."  Wrong, wrong, wrong.  It's not that difficult to improve the quality of data these days. The weapons marketers can use to enrich data include:
(1) Paying external agencies to manually enrich data (very expensive)
(2) Progressively improving the quality of data over time by becoming more robust in making sure members of staff complete records more consistently; some of which can be enforced with changes to software
(3) Exploiting 'big data' to cleanse your data by straining it through a source of 'good data' such as an industry database, consumer insights database or postcode database.

How do I channel dialogue opportunities to encourage sales people to engage customers at the right time and for the right reasons?
Systems like NDMC's LeadGenerator360 enable dealers to upload/mine their existing data from administrative systems and build up a pipeline of reasons to speak to customers when they want you to (I'm sure there are other systems that work in a similar way out there ;-).  Such systems generate a pipeline of reasons to engage customers 'one customer at a time' based on key events like vehicle birthdays, service plan expiries, warranty expiries, MOT reminders etc. that ensure every single worthwhile opportunity to engage customers is not overlooked.  At the same time, leads are allocated and load-balanced in a way that avoids sales people from becoming overburdened. Linking lead pipeline to customer profiling builds a virtuous circle of 'using insights to capture insights' that reduce the need for contact 'expressly to capture data we should already know about our customers' or spurious sales calls that customers hate because they feel they're being sold to.

Where do I start?

The best way to start the journey towards Customer Science based marketing methods like profile and persona building is to perform an audit of the 'net present state' of your customer insights and the extent to which your dealership is exploiting its dealer insights.

NDMC (www.ndmc.uk.com) ... and again, I'm sure there are other supplier companies out there... offer a 'CRM Diagnostic' service and system.  This is a one-time reporting cycle where key data is extracted from existing DMS and administrative systems to a secure space, where it is cleansed, normalized, analyzed, and then - from the connections made in the Customer Science Engine - out pops a series of online (still secure) 'drill-downable' reports and views.  This type of diagnostic service will qualify how complete and consistent the customer data is, and the number of 'meaningful reasons to engage customers' against what the dealership should be capable of based on the size and characteristics of their customer database.

- ends -

The eight word phrase that every salesperson should know

The eight words that every salesperson should know!! The article attached is a fascinating look into how it's possible to invoke positive reactions from people simply by choosing the right words. It's well worth a read for any sales person!

Why behavior change apps fail to change behavior

How often do you 'look up at the sky' in your business?

It's been (almost) full blue sky over Northampton, England this last few days... rare in Britain.  Weather is all too unpredictable in our little backwater of the world which is why we've made it our most prevalent talking point as a nation.  If there was a national pastime beyond gardening it would be talking about the weather!

US Tech Solutions is a global business and so I regularly find myself speaking with guys and girls in India and in the hotter states in the USA like Florida and California.  In those spots I'm sure blue skies day after day are far more common.

I was reflecting on this today... business is a bit like the weather because some days are clear blue skies while other days are far more unpredictable and unpleasant.

I take a regular half hour walk at lunch to make sure I have a clear head for the afternoon session.  During this time I will make an effort to look up at the sky instead of where I'm putting my feet.  I've found this takes a conscious effort.  It's all too easy to look down at the floor and never lift your head. In my reflective moment I wondered if I would bother to look up at the blue sky if it was ALWAYS blue sky.  Would I bother to take notice of it at all if I were in LA, Florida or Pune when in all probability the sky would be completely blue?

Then it struck me (no, not the low hanging branch silly, the THOUGHT).

I'm always working with business people to extract new value from their customer insights and data.  This work typically requires an investment of management capacity on looking inwardly at systems and processes.  But the PURPOSE behind this work is normally to become better at 'listening to customers' and apply the learning lessons. What can happen, and so often does, is that managers start to forget about why they began these projects - somehow the emotional reasons behind such projects can get 'lost' - and one finds the focus of discussion is on IT systems and data... the mechanical stuff.  One reason for this is because business landscapes don't visibly change every second so it can become difficult to justify investing in looking up at the sky.  One has an instinct to concentrate of looking where one is going rather than investing time looking into the distance or up in the air - because it's unlikely to have changed.

And yet...  business is about the small margins.  Competitive advantage is normally found on the fringe of a proposition.  New strategies can come from external impacts that nobody in the management team was looking for.  How do I know this?  Because I've spent a decade helping businesses to find the unusual connections in their data that show real promise for new products and services, new up-sell opportunities and ways to streamline processes to cut costs. Any thoughtful STRETCH STRATEGY focuses 80% on the core and 20% on the margins.

How many of the great game-changing ideas and stretch strategies came from looking 'down at your feet' - where the business is going?  Answer.  Very few indeed.

So please... think about your business day and how much of it is spent looking up to the sky to search for those small differences that have interest.  And if your sky is normally blue anyway, look all the more harder.

Ian.

IS YOUR BUSINESS INTELLIGENCE 'ACTIVE'?

Business Intelligence has been around for decades but it's role is constantly evolving.  At one time the production of a scorecard or set of traffic lights was enough to excite senior managers starved of data analytics.  Increasingly the scope of Business Intelligence has moved towards real-time delivery of fine-grained operational analytics where the production of newsworthy content has become embedded into the operational systems that serves the source data up.

The activity of taking data from multiple sources and building a new suite of 'data cubes' is gradually being overshadowed by BIG DATA possibilities to harvest data on the fly and provide much richer, much more useful insights because the content is fresher and users have more versatile and intuitive tools to ask the questions THEY want to ask - instead of being served up preset report views.

In the last few years we have seen SOCIAL BUSINESS INTELLIGENCE becoming vogue as senior managers seek to socialize performance analysis and reporting; and have more middle-managers, industry partners and members of staff benefit from business performance and activity insights.  This has been encouraged by mobile working and mobile devices that make business intelligence tools more accessible no-matter where people work.

There is another stage on the evolution of BUSINESS INTELLIGENCE that's emerging.  Business managers are coming to realize that 'knowing what you already know' and fashioning it into pretty dashboards isn't the greatest use of BI technology.  What really makes a difference is when managers can answer NEW QUESTIONS and even CREATE QUESTIONS.  But what good is that if you don't have the means to ACT on your learning?  All too frequently, the lessons learned from Business Intelligence result in more additions to the long-tail of demand for new or enhanced applications that can be used to support improved processes, or completely new methods, platforms and processes required to support growth initiatives.

This is where platforms like Encanvas, Spotfire, Jackbe and Outlooksoft really excel becuase they provide companies with federated BI together with the tools to build or improve information systems to meet changing requirements for information.  Few processes thrive without IT to support them these days - and that means no BUSINESS INTELLIGENCE system is complete without the wherewithal to ADAPT information systems as the result of the learning phase.

I think in the next decade we're going to see data visualization tools that are characterized as 'BI' becoming shelf-ware unless they start to embrace the capabilities of agile platforms to build and shape information systems in support of the long-tail of applications demand in the enterprise (and beyond it) without the frictional costs of IT that buyers have to live with today.  What customers really need are not systems that just tell them new news and then don't have any follow-through to enable them to do anything about it.  What they need are ACTIVE Business Intelligence platforms that can LEARN, then APPLY fine-grained, event-driven business insights.

I.

What drives public sector IT buyers?

IDC has authored an interesting article on the buying drivers of public sector IT decision makers.  In their summary they state:

!Western European governments have entered a time of structural volatility that will prompt IT and non-IT executives to look for a better balance between the low cost of ownership of IT solutions at a time of severe budget constraints and the ability to deliver value to business-specific processes and programs. It is in these situations that more detailed segmentations can help ICT suppliers differentiate their go-to-market strategies to gain market share."

Visit the site here: http://www.idc-gi.com/getdoc.jsp?containerId=GIPP03V

Another Blue Ocean Example

It's great to see business people turning business management concepts into reality.

In this case Executive Vice-Chairman A. Vellayan of the Murugappa Group happened upon the Blue Ocean book and tit caught his imagination.  As the head of strategy for the group he decided to put some of the concepts into practice.

A great story!

Read it here.

I.

http://www.thehindubusinessline.com/companies/how-a-blue-ocean-strategy-helped-the-murugappa-group/article4341023.ece

10 Colors That Increase Sales, and Why | Business 2 Community

10 Colors That Increase Sales, and Why | Business 2 Community:

I really like this article.  Any marketer needs to know how colour impacts on readers and Brian tells this story very well.

Enjoy!

I.

BIG TALENT: THE NEXT BIG STEP IN TALENT AGILITY (White Paper)

‘Big Data’ is the latest buzzword in IT. It suggests a collection of data so large and complex that it becomes difficult if not impossible to process using traditional database management tools and applications.  So-called ‘big data’ is the consequence of massive data growth resulting from the globalization of data through the Internet and the paucity of data now being made available via the Internet.  It is both an opportunity and a challenge:

• An opportunity because it has the potential to be a source of fresh insights that individuals and organizations have never been able to source by themselves (perhaps due to the economic costs of data acquisition or simply because they've not previously had access to the data assets). Much of the value of big data comes from harvesting insights that are either richer in quality or content as the result of their source, or are valuable when other ingredients are added.  For example, traffic information can be made more useful when aggregated with road works plans and the movements of major logistics and trucking companies.  This single page view of multiple data-sets builds a richer, more complete perspective on a topic.
• A challenge because big data exists beyond the boundaries of the enterprise and therefore the traditional tools and methods used to manage the security, governance, processing and analysis of small amounts of data simply don’t serve the new needs.

So what lessons can the talent management sector learn from the BIG DATA paradigm – what does it mean to HR strategists, and why do we think at the Workspend Institute that BIG TALENT is the next big step in talent agility?

In this White Paper sponsored by the Workspend Institute, and co-authored with Manoj Agarwal, President  and CEO of US Tech Solutions Inc., we debate the next big trend in workforce agility.

I hope you find it insightful!

I.

White Paper 'BIG TALENT' Manoj Agarwal and Ian Tomlin, The Workspend Institute