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Posts from the ‘Architecture’ Category


Conversational AI driving Screenless UX

Conversational AI is clearly the now and the future.  According to Satya Nadella, “Bots are the new apps.”  In 2019, 33% of US internet users will augment their digital experience using voice assistants.

In 2016, there were 3 million Amazon Echos and limited consumer use cases. Today, there are over 35 million voice-first devices, 100M’s of voice-enabled devices, and consumers are searching for Voice+Visual experiences.  The explosion of consumers expecting voice driven commerce to serve a core demand —  information search, product search and purchase — requires brand new capabilities.

What are conversational bots? Any computer program able to interact or conduct a conversation with a human via auditory or textual method. People enjoy the conversational interface. According to Nielsen, people spend more than 4 hrs per day in communication apps (and growing).

What are conversational (or screenless) experiences? Any voice or text-based experience (such as chatbots or voice assistant apps – Siri, Alexa, Cortona, Google Home) that uses natural language understanding to dialog with users.

[Synonyms: Conversational interface, screenless UX, dialog system, conversational UX, conversational app, conversational commerce, chatbot, chatter-bot, bot]

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Digital and Data Architecture for 2020-2025-2030

Disruptive 3Ms – Mobile, Messaging/NLP and Machine Learning… The future is evolving faster than organizations can adapt or adjust. What seems crazy a few years ago is now reality:

  • In 2004,  the idea that social networks will impact presidential elections by swaying voters would have seemed ludicrous.
  • In 2009, the idea that smartphone coupled with AI/ML/NLP/Vision/Real-time Data will create a broad sharing economy seemed crazy.
  • In 2015, the idea that wearables will one day replace smartphones seems crazy.
  • In 2017, the idea of self-driving cars and trucks on road seemed to be a few decades away, not right around the corner.
  • the fact that we have digital assistants – Alexa, Siri etc. – that are incorporated into everyday life was unfathomable a few years ago.  With messaging emerging as channel of choice for many, and the demand for unique experiences is growing.

The transformation speed and urgency is picking up in almost every industry. 


Many organizations flounder in their digitization efforts not because they lack smart talented people or capability but because they lack clear objectives, leadership, experimental mindset or multi-year roadmaps in aligning messy data silos, legacy applications and infrastructure (and mountains of technical debt) into useful digital architectures -> platforms -> business outcomes.

Every CEO today must have an answer to the question, “What is your digital strategy 3 – 5- 7 years from now? What new capabilities are you creating to compete with digital disruptors?”  The challenge is not just the big picture clarity but the subsequent logical breakdown: Strategy -> Capabilities -> Architecture -> Programs -> Projects -> Applications -> Infrastructure

So the first critical question is: What do you really want to achieve?   WhDigitalRoadmapat are the target set of customer journeys or use cases? What are the target  business outcomes and potential ROI? Increased customer loyalty? Better customer engagement? A greater share of wallet via cross-sell? New customers? Lower attrition? Cheaper and faster targeting?

In other words, what are the relevant use cases? As the adage from “Alice in the Wonderland” goes: if you don’t know where you are going, any road will get you there.

Starting with a clear objective is essential in order to create the right architecture, pick the right tool to solve the right problem.  Some clarity is necessary to drive proof of concepts or even select a technology stack to experiment with.

Consumerization is Driving the Next Generation Architecture

Many enterprises are undergoing a data transformation. Consumerization and evolving customer behavior is forcing companies to change how they market, engage, sell and retain.  

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Robotic Process Automation

“Looking to the future, the next big step will be for the very concept of the “device” to fade away. Over time, the computer itself—whatever its form factor—will be an intelligent assistant helping you. We will move from mobile first to an AI first world.”  – Sundar Pichai, CEO Google

BotReadinessSoftware bots or Robotic process automation (RPA) is becoming   mainstream at leading corporations as C-Suite execs look at next generation digital transformation strategies to do more with less.

High-volume, repeatable tasks within existing processes are slowly but surely being automated by software bots. Bots can perform at or better than humans at repetitive tasks using lookup, scraping tools, recording actions, natural language processing, role based access controls and rules engines.

As a result, there is a growing strategic wave of activity around next generation workforce transformation.  The quest for operational efficiency and competitive pressures is driving this wave. Outsourcing, offshoring strategies have reached the point of diminishing returns so a new frontier enabled by a workforce of software robots is emerging.

The focus is not just on simple tasks like answering the phone in a call-center but on managing complex data-heavy business outcomes, such as NLP driven interactions via chatbots, preventing credit card fraud, or conducting compliance checks.

In the past year, I have seen a massive uptick of interest in RPA. Corporations like Citibank, American Express,  Bank of America are implementing this trend with vendors as they race to cut operating costs and ensure compliance. Everyone under pressure from Amazon is looking for ways to automate faster.

RPA - Areas.PNG

The market opportunity of AI across industries and business processes has been expanding rapidly, with analyst firm IDC predicting that the worldwide content analytics, discovery and cognitive systems software market will grow from US$4.5 billion in 2014 to US$9.2 billion in 2019, with others citing these systems as catalyst to have a US$5 trillion – US$7 trillion potential economic impact by 2025.

Digital robots ∼ Apple Siri, Amazon Echo/Alexa, Microsoft Cortana, IBM Watson, Google Home/DeepMind, Facebook ChatBots, drones and autonomous driverless cars ∼ are now mainstream. What most people are not aware of is the rapidly advancing area of enterprise robots to create a “virtual FTE  workforce” and transform business processes by enabling automation of manual, rules based, back office administrative processes.

This emerging re-engineering of key back-office and front-office operations is called Robotic Process Automation (RPA).  Machine Learning (ML), guided ML, NLP and graph processing are becoming foundations for the next wave of advanced bot use cases. Speech recognition, image processing, translation have gone from demo technology to everyday use in part because of machine learning.

A whole new ecosystem has emerged – Automation Anywhere, Blue Prism, UIPath, Thoughttonomy, Workfusion, Redwood, Kyron Systems, Softomotive, Kofax Kapow and others.

RPA – What?

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Retailers and Data Science, ML, AI

“Shopping is getting personal/easy/fast.  Machine learning is enabling interactions to become more targeted, relevant and intelligent.” Mary Meeker Internet Report 2017 

The challenges facing retailers in the midst of this transformation are legion. Traffic at many shopping centers has dwindled, price competition is heating up, and 100+ million Americans are Amazon Prime customers — locking them into a system where they can get free delivery on millions of items and access to exclusive movies, shows and video games.

It doesn’t take genius to predict that digital induced pain for brick-and-mortar retailers is going to get worse.  The expectation gap between what consumers are expecting from retailers and what they are receiving is getting wider.  Consumers are spreading their buying activity across channels, forcing retailers to spread out their digital investments.  This puts significant stress on execution, product/platform management, design and leadership.

Evidence of this value migration from physical to digital is mounting every day. Against that backdrop, Wal-Mart is closing over 269 stores as it retools portfolio. [Walmart paid more than $3 billion for Jet to speed its data driven digital transformation.  It’s been acquiring smaller players like ModCloth, Moosejaw and Bonobos to appeal to Gen Y and Gen Z segments.] Macy’s said that it will shutter over 36 stores as store traffic declines faster than expected, and Finish Line said that it would close 150 stores by 2020.  Gap,  J.Crew,  American Apparel, Sears and Kmart, Target, Nordstrom are all facing similar headwinds.

Data drives digital transformation.

Starbucks CEO Howard Schultz laid out his thoughts on the future of retail, “three years ago we began to envision that there would be a seismic change in consumer behavior, and that seismic change was due in large part to e-commerce, search and smartphone shopping.”  

It’s fascinating to watch retailers experiment and shift tech/platform strategies to deal with digital disintermediation, showrooming, physical-to-digital channel integration, mobile shoppers, same-day delivery/fulfillment, programmatic targeting, online native models and now the new buzz.. AI and augmented reality.

While most retailers seems to know what to do….they are unable to execute consistently or effectively around more efficient search, pricing, targeting or data mining. A talent gap in many cases. A platform gap in others. Others are hindered by legacy IT apps and infrastructure. Others by silos of data or necessary next generation technology capabilities like A/B testing, data science and machine learning.

This data driven digital retail UX and shopper evolution is a continuation of the trend from 1960s.  

Retail Digital

Analog to data-driven digital transformation

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Digital Journeys

For the times they are a-changin’… Bob Dylan

Customer channel behavior and interaction model is evolvi3 151ng constantly.  Just when retailers, banks and others think they have multi-channel figured out the channel/interaction game is shifting with chatbots, virtual assistants, speech shopping, and other innovation.

New technologies have emerged to
revolutionize the way end-users
interact with technology and to
reshape businesses. According to Gartner: “Conversational AI-first will supersede cloud-first, mobile-first as the most important, high-level imperative for the next 10 years.”

Basically, customers are not interacting with brands in a linear fashion… they are jumping around from channel to channel and expecting the experience to be seamless and relevant.

For instance, in online shopping, women are more likely than men to reach for their smartphones and tablets to research and make purchases. Of U.S consumers who say they’ve completed a purchase on a mobile device in the last month, 66.5% are women and 33.5% are men. Compare that to 2013, when a greater share of men than women completed purchases on mobile. [BusinessInsider, The e-commerce demographic report].

To better understand, customize and respond based on customer behavior/context/clicks, Fortune 500 companies are making large investments around Programmatic Marketing (“Marketing that learns”). Specifically, the objectives are:

  • Visualize and map the 1:1 customer journey by personas.. Customer journeys are an illustration or visual representation of all points of interaction across touchpoints.
  • Optimizing on the right journey attributes to increase yields  by >30% lift… Uncover the right combination of web, mobile and physical channels, content and experiences that  best achieves the target goals
  • Enable marketers to identify journey bottlenecks for individuals and aggregates
  • Leverage actual behavior data to enhance and personalize the experience for each individual customer

One of most often implemented use case in Programmatic Marketing is customer journey mapping and analytics.  Why? Because, deciphering the nuts-and-bolts” of individual customer journeys (and deducing intent) is core to improving customer experience and driving brand loyalty.


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Digitizing Wealth Management – The Rise of Robo-Advisors

Fintech stands for financial technology. It’s just a blanket term for technology that is disrupting the financial services industry. Payments, Blockchain, Robo-Advisors (or automated investment advisory services) are all segments in Fintech.

Why robo-advisors? We are in the early stages of a shift in wealth management, especially “plain vanilla” investing for the mass affluent and millennial segment.  Until recently, you had only two options when investing:

  • Do-it-yourself (DIY)
  • Hire a registered investment advisor (RIA)

Now there is a third option.  Robo-advisors are new a class of financial advisors that provides online, algorithm based portfolio management with minimal human intervention. Robo-Advisors going after the low-end of brokerage/RIA business with automated asset allocation.

The Robo-Advisors market leaders who are serving the mass affluent include are:

  • Wealthfront (with over USD 2.6bn in assets under management (AuM) and 20,000 investors);
  • Betterment (with over USD 1.4bn in AuM and 70,000 investors); and
  •  FutureAdvisor (With over $600 million in AUM).

The timing for this market shift coincides with three trends: consumerization, digital tools, and disillusionment with status-quo investment advisors.  The gyrating stock market driven by program trading is increasingly bringing Robo-Advisors, algorithmic portfolio management to the forefront.  Investors are getting disillusioned with traditional investment advisors who simply track the market indices (SPY, QQQ or Russell 2000) by purchasing ETFs at best.

Many banks and brokerage firms over the years have shifted their focus to serve ultra high net worth (UHNW) and high net worth (HNW) investors, leaving an opportunity for firms to target the “mass affluent” investors, or those with less than $1 million in investable assets. Younger investors are increasingly interested in online digital advice, as opposed to hiring an adviser.

wealthfront3 Read more »


Digital Marketing Architecture: CMO Martech Playbook

“i don’t think retail is dead. Mediocre retail experiences are dead.”   Neil Blumenthal, CEO @ Warby Parker

“In e-commerce, lines are blurring fast across Ads/Content/Products/Transactions.” Mary Meeker, Internet Report, 2017

Seismic shifts are putting customers in control.  New innovations like mobile Augmented Reality (AR), Conversational-AI are changing the landscape of what’s possible in terms of consumer experience.  This is truly an exciting time to be in marketing technology (MarTech) and data-driven marketing. Lot of innovation, experimentation and chaos.

Marketing technology (MarTech) is composed of the following: data, analytics, sales and marketing automation, email, predictive tools, commerce technology, shopper marketing and payments.

MarTechHighLevelWhy this tremendous growth in Martech? The customer lifecycle around acquisition, engagement, commerce and retention is going through a major upheaval. Changing buyer behaviors forced companies to change how they market and sell. Instead of the classic CRM and “inside-out” approaches, a new wave of “outside-in” fresh rethinking around engagement, experience and micro-targeting is taking place.

Chief marketing officers are already outspending CIOs on tech as they race to bring marketing to the B2C and B2B digital world. According to Gartner’s CMO Spend Survey, marketing budgets remain steady at >10% of company revenue. However, the growth and investments are all in digital marketing space as firms focus on millennials,  online customer experience, micro-targeting and multi-channel engagement.

Marketing technology budgets appear to be growing  faster for revenue-related capabilities than more internal efficiency improvements.  Also cutting-edge marketing technology is becoming legacy quickly.  The effectiveness of the generation #1 digital marketing playbook is eroding with mobile-centric usage patterns, ad blockers, and  spam filters. Consumers are now empowered with new and better control over interruptions from marketers. Buying lists, blasting emails, and cold-calling were no longer effective.

A new digital engagement playbook enabled by next generation martech is needed.

Good -> Great… Marketing Technology Architecture

As the race to become digital and engage prospects/customers gains momentum in every industry, CMOs are faced with an interesting challenge they never had to deal with before:

  • What is an efficient and effective digital architecture?
  • What does a “good” architecture look like?
  • What does world-class mean with respect to sales, marketing, service and commerce technology?
  • What is an effective mobile engagement architecture? What is the best way to systematically approach Mobile Onboarding, Activation and Retention (MOAR)?
  • How to make investments that align with a strategic customer engagement plan and not a tactical “plug-the-hole” gap fillers? Read more »

CxO Transformation Dilemma: Digital Businesses and Innovation Clockspeed

“The retail industry is in the midst of a seismic shift. We can bemoan changes in the marketplace or embrace them.”  Target CEO Brian Cornell 

DigitalUnicornsEvery CEO today must have an answer to the question, “What is your digital strategy?”

Consumerization, prosumerism, crowd sourcing, sharing economy, millennial experiences, omni-channel services and other digital-enabled transformations are challenging the status-quo.

Few things have jumped into the consciousness of business executives as quickly as digital business. Executives realize that their companies must succeed in creating transformation through technology, or they’ll face destruction at the hands of their competitors and next generation “unicorns” –  Uber, Airbnb, Netflix,, Pinterest, Google/Nest etc. – that do.

TechTarget’s Tom Goodwin had an insightful observation:  “Uber, the world’s largest taxi company, owns no vehicles. Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. And Airbnb, the world’s largest accommodation provider, owns no real estate. Something interesting is happening.” All are Asset-lite digital businesses.

These new-age firms have an inherent advantage. Digital startups  by their very nature tend to be more user-centric, for several reasons:

  1. They are often founded on the premise of improving or simplifying the lives of end users;
  2. Their business is built from the user’s perspective, rather than on an established business model;
  3. The digital platforms (applications and infrastructure) on which they build their products and services enable a much higher degree of user centrism;
  4. They lack the legacy infrastructures, bureaucracies and operating models that force many traditional companies to continue thinking from the “inside- out” rather than from the “outside-in”.

There in lies the classic Innovator’s Dilemma made famous by Clayton ChristensenRead more »


Customer Engagement Architecture: A Quick Reference Guide

As technology moves faster, customer’s patience grows thinner. A survey from UMass Amherst of 6.7 million users, showed that viewers tend to abandon online videos if they take more than 2 seconds to load. Most users stay on a single web page long enough to read only 20% of the text on that page, according to Nielsen Norman Group.

Instant gratification is the driver of next generation customer engagement architecture. Consumers and customers expect real-time responses. They are being conditioned for this. On an emotional level, posting a Facebook status, a tweet, or an Instagram photo feeds on and reinforces the need for instant approving feedback.  This trend creates incredible challenges for corporations who have to re-engineer, re-factor and re-architect their existing and legacy applications. 

It’s no secret that consumerization is disrupting, eroding and challenging how businesses operate.  Being customer-obsessed or “walking in the customer’s shoes” means putting customers at the core of the business, even if that means disrupting the existing platform architecture.  Easier said than done. In fact, it requires an entirely new engagement toolset at all levels – Systems of Record, Systems of Engagement and Systems of Intelligence.


Yet while most management teams understand the significance of the pace and scale of these customer experience and engagement changes, few companies have determined exactly how their organization’s strategy and architecture needs to change in response.

In response to disruptive digitization vendors have modernized, re-engineered and re-architected comprehensive frameworks to help customers. Here we examine the inter-connected “systems of engagement” and “systems  of intelligence” architecture proposed by various vendors.

  • Customer Architecture
  • Oracle Customer Experience (CX) Framework
  • Teradata’s Interactive Customer Engagement


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Digital Integration Strategies for and Workday

Digital Integration via APIs executes communication between a new generation of SaaS apps (Salesforce, Workday) and the legacy systems of record that provide the data. Legacy apps are “sticky” and expensive/risky to replace. So preserve the old and yet create new value.


Cloud-based service delivery methods  are accelerating in every organization. Simply look at the growing enterprise adoption of Salesforce SFA/CRM, Workday HR, Netsuite ERP, Oracle on Demand, for apps and Amazon Web Services (AWS) for e-commerce.

However the growing adoption creates one of the biggest challenges facing CIOs today – how do you implement new SaaS delivery models while still integrating with the the mission-critical legacy apps you’ve invested in for years?

If SaaS integration is not planned properly, it creates a “cloud in the corner” syndrome – a condition where new cloud-based SaaS solutions are disconnected from existing IT resources. The result: fragmented enterprise data scattered across the cloud.

CIOs have seen this “cloud in the corner” and data silo problem too many times in the past. They know how this movie is likely to unfold. Data quality and integration issues — aggregating data from the myriad sources and services within an organization — are CIOs and IT Architects top concern about SaaS and the main reason they hesitate to adopt it (Data security is another  concern).

Developing strategic (data governance), tactical (consistent data integration requirements) or operational (vendor selection) strategies to deal with this emerging “internal-to-cloud” data quality problem is a growing priority in 2012. Otherwise most enterprises are going to get less than optimal value from various SaaS solutions. Things are likely to get out of control pretty quickly. Read more »

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