Products with personality – the Liquid Big Data customer experience

Digital technology is driving new forms of customer engagement that are rapidly eliminating the functional silos between online and offline retail channels. As a result many high street retailers are already experiencing falling footfall in their physical stores as customers increasingly switch to online competitors for better convenience, choice and prices.

However, these bricks and mortar (B&M) businesses could use Liquid Big Data (cloud-based analytics shared between partners, suppliers and, potentially, competitors for their mutual benefit) to integrate the physical and digital customer experience into a unique, responsive personal customer journey online competitors can’t imitate.

So what might the Liquid Big Data customer experience be like for a global retailer selling ready-to-assemble home furniture, appliances and accessories for example?  Here are some ideas…

An eidetic world

Traditionally high street retailers focus on their brand as a source of differentiation to attract customers to their physical stores. Yet conversely, digital empowers customers to focus on their specific wants or needs regardless of provide. That’s why their online competitors invest so heavily in user experience design to continually optimise how customers use their channels to browse and buy the products they sell – choice and accessibility as a form of differentiation. To combat this challenge, B&M businesses are increasingly using digital technology (such as touch screens, beacons and virtual reality) to differentiate the in-store experience as something equally empowering or seamless as being online.

However, by choosing to replicate the online experience, in-store risks ignoring a source of competitive advantage unique to B&M: a customer’s physical experience with a product and the wider environment.

Using Liquid Big Data, the retail customer experience does not have a beginning or end nor is it location specific – it’s contextual.  Powered by a smartphone app provided by collaborating retailers and suppliers, wearable technology (such as a watch or glasses) could capture the people, places and objects an individual customer likes, loathes or loves throughout their entire lives. Even if such encounters are fleeting, these moments are captured with photographic, eidetic clarity in the individual’s private cloud. The customer can then choose which of these experiences to share with the retailer via the app to create a unique, personalised shopping experience in-store every time they visit.

This could be the raised heartbeat of seeing Rome architecture for the first time – could our example global retailer offer this customer discounts on its in-store Baroque furniture offerings? Another customer loves the feel of velvet – could an in-store sales team member suggest some appropriate soft furnishings? One customer really liked his girlfriend’s coffee table she had at university three years ago – could today’s store visit be an opportunity to find something similar for their new home?

Liquid Big Data enables a high street retailer to use the eidetic physical world as a way to effectively personalise its in-store customer experience using digital technology – enhancing its existing brand as a form of differentiation that can’t be imitated by its online competitors.

Products with personality

Harnessing the power of the eidetic world may not be sufficient long term to differentiate the in-store customer experience versus online. Although it offers a targeted customer experience it doesn’t necessarily make a customer’s relationship any closer or more intimate with the specific products a B&M business sells – a key driver at the heart of the competing online experience.

Yet the customer experience of an online retailer is ultimately a passive, limited engagement typically contingent upon the specific browsing or buying history the customer has with their channel or brand or other self-selecting activity such as social media engagement.

In response, a high street retailer with its partners, suppliers or competitors could use Liquid Big Data to take personalisation to a deeper level – use cloud based artificial intelligence (AI) to create direct relationships between individual customers and the products they sell.

The idea is to personify a product using AI with a user experience similar to smartphone personal assistants or virtual customer service agents. A customer can have a text or voice conversation with the product to explore its suitability for purchase (including reviews or endorsements) and select any desired tailoring or customisation. A customer may also enable the product AI to access his or her eidetic memories or social media profile to help shape and personalise their relationship. The AI can either be used on request or continually available to provide product updates or after sales support. In addition, products may also talk to each other in the cloud as a form of machine learning to identify potential new product designs or opportunities for complements that better meet their individual customers’ needs.

Such insights are then gathered by the retailer and participating stakeholders to inform the customer experience in-store (and beyond), support product development and address any supply chain issues.

For example, our global retailer has found that people across the world keep asking the same question about the performance of a specific brand fridge freezer it sells. Could there be a quality issue with this particular product that needs investigating? Customers in a specific region like the way the product is sold in-store by staff based on their after sales conversation with the AI – how can this be replicated in other regions where demand is falling? The collective cloud AI has also designed a new cooling, energy-efficient feature for the next model – a potential hot seller that could be delivered in collaboration with the supplier?

The potential headline benefits of a high street retailer using the Liquid Big Data customer experience include:

  • Enables new forms of personalisation and innovation deeper than anything previously available in the market by integrating real life and digital customer experience
  • Challenges the seemingly unbreakable competitive advantage of  online retailer competitors and other digital disruptors (such as platforms and social media channels)
  • Links in-store digital technology directly, explicitly with specific customer needs daily – materially lowers the risk of this investment and increase its ROI

If you would like more information about how cloud-enabled big data and analytics can benefit your organisation please contact the Sopra Steria Digital Practice.

Power your competitive advantage using digital thinking

Digital Thinking – the ability to disrupt markets using cloud-enabled big data and analytics capabilities – can positively transform how an organisation differentiates itself from competitors and optimise costs.

So how can an organisation maximise the benefits of Digital Thinking? Here are some ideas…

The Mirror Technique

A digital disruptor turns a sector on its head by making it a lot harder for incumbent players to strategically identify, assess and respond to the threats they pose. For example, Uber, Airbnb and TaskRabbit don’t buy or supply the services in the sectors they compete in – they are not direct competitors in a traditional sense. Rather they are convenient intermediaries that offer both customers and suppliers faster, smarter ways to transact with each other using their own monetised cloud services.

Arguably for many organisations (large and small) Digital Thinking like these outlier disruptors can be challenging, particularly where barriers of entry to their sector are considered to be high. To help validate any threats or opportunities from such market innovation, an organisation can apply “The Mirror Technique” – no matter how impossible or unfeasible it looks, what would be the exact reverse of its current approach to market or operating model? What would be the impact on the organisation and its customers if a direct competitor or new entrant implemented this approach first? And critically, how fast could available cloud capabilities realise these potential disruptive forms of competitive advantage?

This application of scenario analysis can help an organisation identify and assess the risks and opportunities it faces from previously unforeseen cloud-powered Digital Thinking – could it be standing on a burning platform or an untapped goldmine?

Big Data Learning

Gathering large volumes of unique data about customers and operating model performance is emerging as a key source of competitive advantage for many organisations. For example, UK high street retailers are capturing data about customer buying behaviours across their physical/in-store and online channels to better personalise their offerings against the experience delivered by Digital Disruptors like Amazon.

A key challenge is learning how to yield these disjointed, complex data sets into something coherent that delivers effective moments of delight for an individual customer using an efficient value chain. Furthermore, by an organisation treating its big data capability as a barrier of entry for competitors, there is a risk of delaying the time to market of any resulting initiatives because it’s having to learn by itself, in isolation, how best to use this form of Digital Thinking.

One way to potentially accelerate and de-risk this learning process is to for an organisation to collaborate with its partners or suppliers in the gathering and application of big data using a cloud platform. In addition, it may even want to consider coopetition with its competitors where participants share their experiences and capabilities together for mutual benefit – “Big Data Learning” enables greater competitive advantage for all the more its shared.

The face to face test

Digital disruptors exploit analytics to inform the design of new forms of personalised engagement including customer centricity, social media and media content. Combined with their ability to offer competing services with lower (or even zero) switching costs for customers; such Digital Thinking risks rendering an organisation’s established market offerings obsolete.

Another outlier disruptor vividly illustrates the competitive advantage of such a move – FaceBook’s $16 billion acquisition of cross-platform mobile messaging service WhatsApp. Not only has WhatsApp decimated Telcos’ revenues from text messaging services, these incumbent players will have no direct access to this huge Social Media channel (estimated 900 million global user base) and the customer insights it generates – Facebook is using Digital Thinking to create an unbeatable barrier of entry as well using this unique analytical capability as a platform for future growth.

However, unlike many traditional organisations, disruptors arguably have no experience of physically serving customers directly to inform these capabilities. This weakness can be exploited by using “The Face To Face Test”, where an organisation applies its own tacit, historic experience of customer engagement to develop a new disruptive market approach using analytics. This test asks questions about how one of their own real life customers would react if a digital service was delivered to them physically by an employee. Example questions include: what information should your employee intuitively, instinctively know about this individual customer before they start serving them? What things shouldn’t they know or ask about? How can your employee genuinely surprise and delight this long standing customer every time?

By applying analytics as a representation of a physical employee drawing from real world experience, an organisation can arguably personalise their customer engagement approach in ways beyond the reach of digital disruptors.

If you would like more information about how cloud-enabled big data and analytics can benefit your organisation please contact the Sopra Steria Digital Practice.

Broaching the final frontier of unstructured data – the contents of our heads

When asked what we want, most of us struggle to break free from the chains of practicality. This default mental setting provides a defence against disappointment, but also a limit to progress.

For example, if you ask marketers what customer insights they would like, the likely response is a better version – more complete, accurate, timely, granular – of what they already have. But if asked for an idealised list – no constraints – then the list would look very different. The dream for any marketer would be to know at any given moment what each customer wants to feel or be, what they think they need to do or own to achieve that objective, how they plan to act so as to make it happen, how much they are prepared to spend, how far are they prepared to search or travel, etc. Think of the type of insights you would get if you had sensors reading the thoughts, perceptions, hopes, fears, ideals and ideas in every potential customer’s head.

Far fetched? Less than you might think thanks to digital technology.

We already have a sensor semi-permanently attached to our fingertips in the form of a smartphone; and increasingly ones attached to our wrists or faces in the form of smart watches and smart glasses.  (As a result mobile operators will take an increasing share of the customer insight value chain from traditional market research techniques, possibly even creating the next giant of the analytics industry in the process if one of the leaders successfully emulates what Tesco achieved.)

Equally, via social media people have the opportunity to express their happiness and frustration (and other emotions) as they are experiencing them while sharing what they are experiencing via photos or live streaming.

Finally, there is gamification.  Social gaming sites provide a real live environment for testing ideas with target customer groups to yield instinctive responses (those that dictate purchase behaviour for many products) rather than the considered responses that survey-based research typically yields.  Gamification techniques can also be used within surveys to increase both response levels and quality.

How gamification can help businesses glean insights from the final frontier of unstructured data – the contents of our heads – is the subject of a further article on insight advantage… coming soon.

What do you think? Leave a reply below or contact me by email.

An ugly word, but the source of all human progress

‘Datafication’ is a newly invented word, and like many of that ilk it is painful on the ear and embarrassing on the tongue. But for all its ugliness, what it describes – the creation of data through the extraction of measurable features from the unstructured information that surrounds us and quantifying, classifying or categorising them – is arguably the single biggest contributor to human progress.  Datafication has delivered the numeral system, maps and double-entry book-keeping; underpins the scientific method, statistical inference and ratio visualisations; without which the world we live in would be far less advanced.

“So what?”, you may say. These things were happening long before a few neurons got overexcited and the word datafication was born. Why is it important?

The simple answer is that in the digital age the rate of datafication is accelerating.  The ability to capture information from the world around us via digital technology, quantify it and pattern match it with other data is unprecedented. These new forms of data will become an increasingly important source as we seek to predict rather than simply understand. As any data scientist will tell you, the broader and more complete the set of data a model is based on, the more accurate it will be.

Even something as abstract as human behaviour can be quantified; how is covered in my latest article on insight advantage.

In this article, I use the example of someone being interviewed regarding a crime, but the same principles apply in different situations, for example to identify genuine buyers who need help in making their purchase decision from browsers who have no intention of buying and where sales effort will be wasted or shoplifters who need to be encouraged to leave. More obviously the same applies with on-line behaviour. And the organisations that are best able to collect and analyse this diffuse information about customer behaviours will be the ones that end up with insight advantage.

What are your thoughts? Leave a reply below or contact me by email.

Data: exhaust rather than oil but key to turbocharging performance

My likening data to a by-product of combustion rather than its fuel may seem strange, especially as I have argued that superior data-driven insight is the most sustainable source of competitive advantage in the knowledge economy.

Analogies can help our thinking in two ways – firstly grabbing attention to change a mind set; secondly changing the way we think to support behaviour changes. In the context of the latter, analogies are a staple for therapists – as anyone who has recently visited a physio or other therapist will probably remember. And given the continuing need for organisations to change – whether by continuous improvement or more radical transformation – analogies of the second type are a valuable enabler in business.

Data as the new oil fits into the first type of analogy. It’s memorable, signals value (both fuel and lubricant to the global economy) with some eco-friendly overtones (the age of oil is over). So it stands out. But does it help beyond that?  Not really.  There may appear to be some mileage in the refining idea. But crude oil is refined into multiple different products – jet fuel at the top end of the quality spectrum and bitumen at the bottom with petrol, diesel, gas, lubricants, marine fuel and liquified gas coming somewhere in between – all of which are then sold to different types of customers. Outside organisations that specialise in data monetisation, the data as oil analogy doesn’t really stretch into anything that has practical application.

A far more useful analogy is seeing data as digital exhaust. Automotive exhaust was originally collected and treated in catalytic converters to meet emission controls. Similarly data in organisations has traditionally been collected to meet regulatory requirements – financial reporting, compliance, etc. Catalytic converters were replaced by turbochargers which didn’t just ensure that regulatory requirements were met, they recycled exhaust emissions to improve performance.  And turbocharging technology has developed to such a level that a small car can achieve 60 mpg driving across a town while emitting cleaner air than it takes in.

In the case of digital exhaust, the turbocharger age is just beginning.  The organisations who achieve superior performance will be the ones that recycle data most effectively to reduce costs while providing a superior experience to customers (and other stakeholders), differentiating them from competitors and driving growth in revenues and investment returns.

Read my article describing how businesses can build a data turbocharger to enable insight advantage can be found here:

What are your views? Leave  a reply below or contact me by email
photo credit: TURBO R via photopin (license)

Blending Kipling with stakeholders to gain Insight Advantage

Rudyard Kipling is an unlikely candidate as a guru of Insight Advantage. But as a Nobel Laureate for Literature, he understood the role curiosity plays in firing the imagination. Both curiosity and imagination are as important now as when Kipling was at his creative peak and wrote “I keep six honest serving-men” – essentially his recipe for creativity.

In our white paper on How to Improve Business Performance with POST-Digital Capabilities, Elliot Howard, John Batchelor and I outlined the importance of customer curiosity, a term first coined by Elliot. We wrote:

“Customer curiosity extends beyond simple customer centricity, it incorporates constant focus on improving insights into customers so that why they behave as they do is as well understood as the more easily identified what, where, when and how elements of behaviour. It requires a culture of experimentation. Experiments create new data and new insights. And ultimately customer curiosity is about creating an increasingly rich data profile for each customer.”

In essence, customer curiosity boils down to asking questions – more importantly, asking the right questions. And while customers are the most important stakeholder group a business has, they are not the only one. Insight Advantage stems from curiosity about each stakeholder group – how they can be better served and gain created as a result.

The second article in my series on Insight Advantage describes how you can blend Kipling’s honest serving-men with stakeholder theory to identify the questions that you should be asking, rather than simply asking the ones that you know can be readily answered.

What do you think? Leave a comment below or contact me by email.

Changing the conversation from Big Data to insight advantage

With Big Data once again we in the IT industry are falling into the same old trap of talking about inputs (volume, velocity, variety and veracity) and technology (Hadoop, Spark) rather than the desired outcomes. No wonder then that analyst groups are reporting that only a tiny fraction of Big Data proofs of concept are being industrialised and put into production.

On one level this is understandable – talking about outcomes can seem a little dry.  Highlighting the potential for revenue gains or cost savings or reducing risk (of future costs or revenue losses); or indeed the underlying elements – such as operational excellence or an enhanced customer experience – that will deliver those financial gains can seem as if the same old story is being recycled. Consequently it is much more exciting to talk about what is new, which is why the technology always seems so exciting.

But this time there is a difference. We live in the information age and work in the knowledge economy. Insight is the lubricant of both and the most sustainable advantage any business can have is better insight than its competitors. And by better I mean in breadth, depth, accuracy and timeliness.

The good thing about Big Data is that data – the raw material for insight – is in vogue when for ages it has just been seen as digital exhaust. But to make the most of the transformational opportunity that is available, we need to steer the conversation away from Big Data to what it enables, strategically. We need to use the excitement about unstructured data and the internet of things to seed the concept of insight advantage in commercial consciousness.

I believe there are six steps to achieving insight advantage. Read my article outlining those steps – the first in a series of pieces that will be published over the next couple of months.