“AI Neutrality”: A proposed manifesto for artificial intelligence user experience design

What makes a great artificial intelligence (AI) driven user experience? Here are my thoughts…

1. Design AI services end to end – the disruptors that have transformed the travel, holiday and retail sectors over the last twenty years succeeded by focusing aggressively on improving their own single channel online experience. AI user experience design must also adopt this strict one channel approach to service delivery – every user journey should be simple, relevant, no fuss and always getting better because it’s being delivered by an artificial intelligence end to end.

2. Go beyond mobile  The interconnectivity of AI enables any environment or physical object to positively affect all of our five senses (such as connected home technology like heating and lighting devices that responds to a user’s mood). AI design should always be pushing to transcend the user interface constraints of existing service platforms (particularly the visual and audio experience of mobile) to truly reflect and improve how we use our senses to interact with the world around us.

3. Addressable media is a key user journey –  AI has the potential to utilise a complex range of historic and contextual customer data to deliver targeted, personalised advertising – for example, UK broadcasters are adopting programmatic technology to deliver specific adverts at individual households in real time. Yet if designed poorly such disruptive engagement risks coming across like hard selling that overwhelms or irritates a customer (consider the negative reaction of customers to pop up web ads that apply a similar approach). Consequently, it’s vital that AI driven addressable media is treated as a form of user experience that requires research, design and testing to ensure customers are empowered to consume it on their own terms.

4. Hardwire ethics and sustainability –  the positive disruption to our lives from social media has enabled these services to grow rapidly and organically by billions of users worldwide. Yet this has also led to these platforms becoming so big it’s challenging for their service providers to effectively manage and safeguard the user content they share. Drawing from this experience, and combined with public calls for the proactive regulation of AI, it’s essential artificial intelligence products and services have the right ethics and sustainability values in their core design as they are likely to grow even faster and bigger than social media.

5. Champion “AI Neutrality” – artificial intelligence has the power to transform all our lives like the internet before it. A fundamental principle driving the success of the web has been “net neutrality” – that internet data services should be supplied as a form of utility (like electricity, gas, water) in a non-discriminatory way to all customers. Access to simple AI services should be similarly “neutral” – a basic human right that is complemented by differentiated, chargeable products and services from over-the-top producers.

If you would like more information about how artificial intelligence can benefit your business, please leave a reply below or contact me by email.

Shopping with Artificial Intelligence: The frictionless family customer experience?

With Amazon, Facebook and Google all adopting an open source approach to development of their artificial intelligence (AI) services, what could this innovation mean for a family shopping on the High Street? Here are some ideas…

An end to Saturday morning parking mayhem – having to spend half an hour queuing to get into a shopping centre car park only to find out the only spaces left are on the hundredth floor can be a miserable start (and end) to a Saturday shop for the whole family.

An AI personal assistant could reduce the friction of this inconvenience by reserving a suitable car parking space at the shopping centre in advance, based on the family’s store preferences, accessibility requirements and other factors, like forecast weather. It can then send the reserved space location to the family’s in-car GPS and automatically pay for its ticket. The more an AI can effectively integrate or communicate with other systems the greater the convenience for customers.

No more bored kids looking at their mobiles – the family have spent hours traipsing from store to store failing to be engaged by any of these retail experiences. The kids are just itching to get their phones out to start socialising with their friends, and mum and dad are getting the feeling they are better off buying online.

An AI could transform the friction of this irrelevant customer experience by giving in-store products ‘personality’ –  a product can introduce itself using spoken voice to these customers (via a store branded mobile app for example), talk about its unique selling points and answer potentially any question about its suitability – all personalised using buying and social insights the AI has about the family. The more an AI can effectively apply analytics to create experiential, contextual shopping experiences, the more compelling and delightful bricks and mortar stores become for customers.

Empowered shopping without added wrinkles – So the family have found things they need and discovered lots of things they want, but mum and dad aren’t comfortable with uncontrolled spending across their bulging wallet of bank cards.

An AI could help remove the friction of this uncertainty by acting as a single channel for these customers to manage their disparate bank services in one place, giving on the spot advice about saving and spending to enable the right purchasing decisions and provide a secure, easy to use payment system using customer voice recognition (biometric authentication). The more an AI can create a platform that combines and simplifies a range of complex services; the better mobility customers have on the High Street – experiences that rival anything offered by online retailers.

If you would like more information about how digital transformation can benefit your organisation please contact the Sopra Steria Digital Practice.

 

Personalisation of the retail returns experience: a new form of competitive advantage?

UK retailers are losing billions of pounds a year from managing reverse logistics costs for returned items across their physical and digital channels. Because of the multiple touch points involved margin can often deteriorate to a point where writing off the item as a loss is a better outcome than resell.

A key area of risk is online women’s fashion retail where customers may order multiple sizes or variations of the same item and then return those that don’t meet requirements. It’s estimated on average a returned clothing item costs a retailer an additional £15 to process back through its supply chain regardless of channel – extra cost that significantly reduces margin at full price (and much worse when further price discounting is applied).

But could personalisation (the application of big data analytics to pro-actively meet an individual customer’s changing needs) deliver a better outcome for both customer and retailer? Could such an approach incentivise a customer to self-manage the reverse logistics process or even be persuaded to keep the unwanted item (so reducing, or even eliminating, the additional £15 cost)?

For example, rather than a customer filling out a paper form using a nondescript reason code for a return, he or she could use a loyalty card smartphone app that captures their reasons as spoken voice text. Not only would this be more convenient (and user friendly) than form filling, it also provides the retailer with richer data about a customer’s preferences to enable better targeted personalised offerings in the future.

Secondly, the app could lever cloud big data analytics to make an on the spot personalised counter offer to the customer alongside the standard return. This could draw from the customer’s buying history and social media behaviour. The counter offer could ask the customer to give the item to charity in exchange for a future discount (so eliminating the return cost and refund while driving future sales and positive brand reputation). Alternatively it may make a third party offer for a ‘no return’ outcome (so driving cross- or up-sell opportunities with little cost impact).

Fundamentally, the counter offer approach is primarily driven by the need to preserve and, ideally, grow a retailer’s margin – the economic case. In addition, by gathering better data about an individual enables greater personalisation to build and retain their loyalty and reduce the volume of unwanted items (for example, future purchasing of clothing items online may include specific recommendations for an individual customer about size and colour based on this gathered insight). The app could also utilise a retailer’s existing core systems (e.g. databases) and new digital technology (such as cloud analytics or machine learning) together successfully – the opportunity to use the best of both worlds to create disruptive competitive advantage.

If you would like more information about how Sopra Steria can help your organisation benefit from cloud analytics please contact the Sopra Steria Digital Practice.

Convenience, Integration, Context: the retail store experience 2020?

As retailers exploit the opportunities offered by digital technology and ways of working to innovate their in-store customer experience; what might this look and feel like in 2020? Here are some ideas…

Convenience: The way customers physically purchase products will be as seamless as any digital channel experience and critically will encourage them not to use their smartphone (a distraction from the real world in-store environment that also brings competitors’ offerings within easy reach). In 2020, a customer can simply touch a button on the product itself or its point of sale display to purchase it instantly – like a biometric version of Amazon’s Dash Button technology that carries out the transaction authorised by the customer’s fingerprint. This simple, convenient process also means a customer doesn’t have the hassle of queuing up at a till – freeing up their time to explore the physical retail space further.

Integration:  Delivery of purchased in-store products will rival any experience an online retailer can offer. Content such as films, music, books are downloaded immediately to the customer’s device of choice. Large and small physical goods can be dispatched from a warehouse and delivered direct to a customer’s home the same day (a service available today that is rapidly growing in scale led by retailers such as Argos). And because items can be sourced direct from distribution; the Retailer can lever greater supply chain efficiencies (such as reduced in-store inventory costs) to drive competitive, dynamic pricing to continually challenge competitors.

High Street retailers are already using cloud-driven big data analytics to accelerate and rationalise their own supply chain operations (for example, Zara levers such capabilities to achieve product lead times as short as two weeks from catwalk design to store). Further application of this “tech company” approach to achieve deeper supply chain and channel management integration could enable a fully converged physical and digital retail experience in 2020 that constantly exceeds customer expectations.

Context: Relevance with be a key way the in-store experience differentiates itself from digital-only channels in 2020. Whereas online personalisation arguably means funnelling a customer to a specific area of interest, a High Street retailer can also use other dynamic data and insights to enrich and contextualise this experience to create unique moments of delight only possible in the physical store environment.

By a customer choosing to share data (such as transmitting their location via their mobile’s Bluetooth capability to in-store beacons), the retailer can identify what product ranges he or she is browsing to trigger nearby interactive display screens that present more in-depth information about those items, share social media content such as user reviews or allocate a sales person to provide advice. Because the customer is in the physical retail space they are in complete control of their personalised shopping experience – moving to areas of interest based on their emotional reaction to the world around them without the limitations or constraints of a smartphone user interface. Nike’s emerging Fuel Station interactive store concept, where customers can choose to engage in different contextual situations (such as having their running style analysed when using an in-store treadmill to identify the right running shoes to enhance their performance) is one example of the potential power of in-store contextualisation that can’t be replicated digitally.

If you would like more information about how Sopra Steria can help your organisation benefit from digital transformation please contact the Sopra Steria Digital Practice.

Four forces disrupting retail today and ways to respond

Incumbents and new players alike are exploiting digital ways of working and technology to create new forms of competitive advantage. Here are some examples impacting retailers today…

  1. CX shifters positively change customer behaviour to drive wider engagement and sales – often through encouraging new forms of brand advocacy and self service that increase wider demand while lowering lower costs. Domino’s Australia applied this form of social commerce innovation to successfully create its Pizza Mogul campaign; where customers designed their own pizzas, self promoted their creations on social media and then shared in a percentage of any revenues generated from Domino’s selling them. An estimated 15% plus revenue growth for Domino’s Australia was attributed to this initiative by the end of last year.One approach for retailers with limited experience of such disruptive customer experience design is to engage tech start-ups to jointly create new forms of market engagement unique to its brand (with John Lewis’ JLAB initiative being one such example). Such an approach can accelerate the “ideation process” although scaling these opportunities to the level or volume required for market use can be challenging given start-ups may lack the experience or capabilities for such rapid industrialisation.
  2. Agile SCM operators combine big data and analytics with traditional just-in-time production and distribution methods to optimise their supply chains. Zara’s “rapid fashion, minimal inventory” approach levers such capabilities to control and drive synergies across its own supply chain that often results in lead times as little as two weeks from catwalk design to production to distribution of a garment to its physical and online retail stores. This disruptive approach has helped Zara become one of the world’s leading fashion retailers with a presence in over 80 countries.One competitive response to challenge Zara is to adopt “fully linked collaboration” supply chain management; where retailers and suppliers use cloud platform technology to openly share data and other capabilities to deliver goods and services together. However to be successful this may require radical new ways of working such as co-opetition between competitors for their shared mutual benefit.
  3. Instant branders use their high recognition, flexible brands to drive successful market penetration of their diversified products or services as sources of rapid growth. One such example is Amazon Web Services that not only powers Amazon’s retail business; it has also fast become the dominant provider for B2C cloud infrastructure services with a 25% worldwide market share reportedly gained over the last five years.Responding to these challengers can mean an organisation completely redefining itself as a “tech company” where its operating model is primarily focused on using technology driven innovation to differentiate and cost optimise its products or services.  Such an approach is core to the success of “Digital Disruptors” such as Uber and Airbnb where they established their own global enterprise platform brands to penetrate B2C markets in different geographies simultaneously. However, these new entrants did not need to transform their existing technology, processes or culture first to be successful unlike existing market players.
  4. Price racers lever their bulk buying power and other supply chain economies of scale to lower prices for targeted quality products to challenge established competitors. The discount supermarkets Aldi and Lidl have applied this model to grow faster than the “big four” UK supermarkets including opening more new stores than these established players combined during the last year.One way to challenge these discounters is to offer competitive prices with greater convenience – same day grocer delivery at home (a model currently being piloted in the UK market by AmazonFresh).  However, effectively delivering this complex supply chain and distribution of potentially hundreds of product lines from multiple suppliers is challenging; it took Ocado over a decade to turn a profit using a similar model. In addition, successfully replicating an individual customer’s preferences for picking fresh goods in-store arguably requires more sophisticated personalised experiences using emerging digital technologies such as big data analytics or even virtual reality.

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

If you would like more information about how Digital Transformation can benefit your organisation please contact the Sopra Steria Digital Practice.

Teachable Brand AI – a new form of personalised retail customer experience?

Within the next five years, scalable artificial intelligence in the cloud – Brand AI – could potentially transform how retailers use personalisation to make every store visit a memorable, exclusive customer experience distinct from anything a competing digital disruptor could offer.

Arguably the success of this engagement approach is contingent upon a retailer’s ability to combine a range of data sources (such as social media behaviour, loyalty card history, product feedback) with its analytics capabilities to create personalised moments of delight in-store dynamically for an individual customer that drives their decision to purchase.

But could the truly disruptive approach be one where a customer is continually teaching the Brand AI directly about their wants or needs as part of their long-term personal relationship with a retailer?

Could this deliver new forms of customer intimacy online competitors can’t imitate? Here are some ideas…

  • Pre visit: Using an existing instant messaging app the customer likes (such as WhatsApp or Skype), he or she tells the Brand AI about their communication preferences (time, date, etc) and what content about a specific retailer’s products or services (such as promotions or new releases) they are interested in. This ongoing relationship can be changed any time by the customer and be pro-active or reactive – the customer may set the preference that the Brand AI only engages them when they are located within a mile of a retailer’s store or one week before a family member’s birthday, for example. Teachable Brand AI empowers the customer to be in complete control of their own personalised journey with a retailer’s brand.
  • In store: The Brand AI can communicate directly with in-store sales staff about a customer’s wants or needs that specific day to maximise the value of this human interaction, provide on-the-spot guidance and critical feedback about physical products their customer is browsing to drive a purchasing decision, or dynamically tailor/customise in-store digital experiences such as virtual reality or media walls to create genuine moments of customer delight. Teachable Brand AI has learned directly from the customer about what excites them and uses this deep insight to deliver a highly differentiated, in-store experience online competitors can’t imitate.
  • Post purchase: The customer can ask the Brand AI to register any warranties, guarantees or other after sales support or offers for their purchased good automatically. In addition, the customer can ask the Brand AI to arrange to return the good if unsatisfied or found faulty – to help ensure revenue retention a replacement or alternative is immediately suggested that can be exchanged at the customer’s own home or other convenient location. The customer can also share any feedback they want about their purchase at any time – Teachable Brand AI is driving customer retention and also gathering further data and insights to enable greater personalisation of the pre visit and in-store experience.

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

 

Brand AI: The invisible omni-channel for retailers?

Digital can pose a range of risks for a bricks and mortar (B&M) retailer including:

  • Declining market share as customer loyalty to its established, traditional brand is eroded away by disruptive new on-line entrants and more innovative high street competitors
  • Poor ROI from implementing new in-store digital technologies because they fail to create a superior personalised customer experience across its physical and online channels
  • The inability to deliver better inventory management using big data and analytics due to immature organisational capabilities in these areas across its supply chain

So how could scalable retail artificial intelligence in the cloud – Brand AI – potentially turn these challenges into unique opportunities for competitive advantage during the next five years? Here are some disruptive ideas…

Brand AI as a personal human relationship

A retailer could personify its brand as a virtual customer assistant accessible anywhere, anytime using voice and text commands from a mobile device. But unlike today’s arguably bland, soulless smartphone versions that focus on delivering simple functionality, Brand AI would have a unique, human character that reflects the retailer’s values to inform its interactions and maturing relationship with an individual customer. Intended to be more than another ‘digital novelty’, this disruptive form of customer engagement builds on and enhances a B&M’s traditional brand as a trusted long-term friend throughout the entire customer journey by offering compelling, timely presale insights, instant payment processing and effective after sales support and care.

Brand AI as an invisible omni-channel

A customer is empowered to select what personal data they choose to share (or keep private) with the Brand AI to enrich their relationship. Social, location, wearable or browsing and buying behaviour data from complementary or even competing retailers could, potentially, be shared via its cloud platform. The Brand AI can analyse this liquid big data using its machine-learning capabilities to create dynamic real-time personalised actionable insights seamlessly across a customer’s physical and digital experience – it is the heartbeat of the retailer’s invisible omni-channel offering.

Critically, Brand AI can transform every retail store visit into a memorable, exclusive customer experience distinct from anything a competing digital disruptor could offer. For example, the Brand AI can advise in-store sales staff in advance what specific products a customer wants or needs that particular day to help personalise this human interaction, provide on-the-spot guidance and critical feedback about products available immediately to drive a purchasing decision, or tailor in-store digital experiences such as virtual reality or media walls to create genuine moments of customer delight. In addition, the AI can capture the customer’s emotional and physical reactions via wearables to these experiences (such as a raised heartbeat when seeing a new product for the first time). Such insights can then be explored later by the customer (including socially with family and friends) using the AI on the retailer’s integrated digital channel to sustain their retention.

Brand AI as an operating model

A further opportunity for using Brand AI is its potential ability to streamline inventory management to improve the customer experience and reduce operating risk. Key processes such as store returns and transfers could benefit from such an approach – not only would the invisible omni-channel AI enable a customer to easily raise the need to return goods, it can also capture the specific reasons why this is happening (rather than this information having to be interpreted by different customer service staff using prescriptive reason codes, for example). Also because the Brand AI has an established personal relationship with the customer it can proactively order a replacement for home delivery or pick up (store or other convenient location) or suggest a suitable alternative product or other cross-sell opportunities to keep the customer satisfied and minimise revenue losses for the retailer.

Managers can also use the AI to help interrogate and identify trends from this complex dataset on returns and transfers. Inventory management reporting and insights are available on demand in a manager or team’s preferred format (such as data visualisation) to support stock purchasing decisions, resolution of supply chain performance issues or investigate region or store specific fraud and theft. And because these analytics are running in the cloud they can be aligned to existing organisational capabilities in this area.

The illustrative benefits for a bricks and mortar retailer using scalable artificial intelligence in the cloud (Brand AI) potentially during the next five years include:

  • Refreshes the competitive advantages of an established, traditional high street retail brand using new disruptive forms of marketing and customer advocacy
  • Materially de-risks strategic investment in new in-store digital technologies by explicitly linking these capabilities to an holistic, long-term customer experience
  • Can improve organisational agility using big data and analytic capabilities to improve existing business processes that directly benefit the retailer and its customers

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