What to Do First When Upgrading Your Call Center in a Crisis

How to Improve Your Call Center Today

This is the second in a series of blogs about improving your call center.

When a hospital, clinic or medical practice gets flooded with calls from worried patients, it’s only natural to think automation is the answer. If a bot can handle the easiest calls, the reasoning goes, then the humans can spend more time answering questions that befuddle the smartest learning algorithms.

A new breed of tools called Intelligent Virtual Assistants (IVAs) can indeed transform your patient-support experience. The trouble is that for all the advantages of IVAs (which are abundant), they can’t cure today’s crush of patient calls because:

  • It can take a month or longer to get an IVA system up and running. Most medical firms can’t wait that long in the middle of a public health emergency.
  • Going all-in with IVAs too quickly can be risky. Trying to do too many things at once can mess up everything.
  • IVAs require a substantial dataset to train their algorithms to translate the content of human conversations into signals of human intent. It takes time to build up that dataset.

These challenges underscore the value of thinking in terms of a journey to IVA functionality that starts out simple by automating a single communication channel. Once you’ve done that, then you can move to automating multiple channels and then, finally, implementing a robust IVA solution.

Automating Your First Communication Channel

Let’s say you’re getting about three-quarters of your patient communications from three channels: voice phone calls, text messages and a web input form. The other one-quarter comes from channels like social media and popular chatting platforms.

You want to pick a channel that gets enough usage to provide valuable data but is still fairly easy to automate. This channel also should carry the lowest risk of unexpected glitches angering large numbers of patients.

Often, a webchat is a useful starting point. An automated script can answer the easiest questions like “what are your office hours?” or “where do I go to schedule an appointment?” Just being able to automate a of couple of common questions takes some of the load off of your human patient-support team.

This gives you help when you and your patients need it most — without an extended wait for a full IVA system.

Moreover, within hours you’ll start getting precious data signaling patients’ intent. Learning algorithms can be trained to identify the patterns in people’s questions. As the algorithms build a massive dataset of right and wrong answers, they teach themselves to anticipate people’s desires and serve them even better.

Training data from people’s questions and other online behaviors makes artificial intelligence and machine learning possible. In the weeks and months to come, you’ll feed more and more training data into newly automated channels that will form the bedrock of a full-functioning IVA system.

A Partner for Your IVA Journey

A simple chatbot can get you on the road to IVA functionality and leave you better prepared for the next new influx of patient calls.

At DMI, we’ve implemented IVAs in a range of sectors including health care, finance and government. We have a deep, rich pool of talent in business consulting, automation, system architecture, machine learning, data science and customer experience. We also use Agile methodologies to get the optimum solution into our clients’ hands in tight time frames.

These skills make all the difference when your call center is at risk of being overwhelmed.

–Niraj Patel, director, artificial intelligence

 

Top 7 Things to Watch When Moving from a Legacy Commerce Platform to the Cloud

Top 7 Things to Watch When Moving from a Legacy Commerce Platform to the Cloud

When a company first decides to move their commerce platform and supporting toolsets to the cloud, they typically focus most of their attention on deciding what type of cloud (private/public) and provider (AWS, GCP, Azure) they want, and then picking the supporting technologies (Spring Boot, Node.js, React, Kubernetes, etc.).

While these choices are important, they are actually less impactful to a successful migration than you might suspect. All of the providers and supporting technologies are mature: They provide what is required for a commerce platform to run in the cloud. Quite often, it’s the things that don’t get the attention they deserve — or get overlooked entirely — that can make or break a migration project.

This blog covers seven of these often-overlooked factors. The advice below applies to two common scenarios: Working with cloud-based components you own or manage, or interacting with third-party cloud components.

Whichever way you go, you need to pay close attention to these points:

  1. Strategy and roadmap. It’s imperative to develop a robust plan to coordinate the activities of team leaders, system architects, database administrators, coders and support personnel and have everyone aligned on the overall project strategy and roadmap. Also, understanding the TCO, ROI, and hard and soft savings should be included in the planning.
  2. Skillset management. Cloud components require specific skills and experience. VMware skills don’t always translate into Google Cloud skills. You have to address skill deficiencies as early as possible and manage them carefully before, during and after the cloud transition.
  3. DevOps. To get the most value from cloud e-commerce, you need a nimble development process and rapid software updates. Following DevOps principles and putting the design and architecture in place up-front in the migration helps keep all your moving parts coordinated.
  4. Performance. It is assumed that moving to an elastic, cloud-based environment with modern technology will improve performance. This is not always the case with both cloud platforms and headless architectures for ecommerce systems. After you have made the investment and delivered the project, the customer experience may in fact be worse if specific steps are not taken up front to optimize page performance. In addition, slow-loading pages can wreak havoc with search engine rankings. Designing and optimizing for performance up-front is mandatory.
  5. Monitoring. Because cloud components are beyond your direct control and somewhat abstracted, you need a comprehensive system monitoring setup. This includes monitoring, logging and alerting that will get people moving and enable them to fix problems as soon as possible.
  6. Design patterns. You must decide how to design the components of the platform. Cloud-based computing provides more flexibility and choices in design patterns, so defining and aligning all teams on the overall design patterns to be used will allow you to create a more cohesive, well-designed platform. Left to their own devices, different teams may end up building things in different ways, producing a confusing, convoluted cloud implementation. You need standard, coordinated design patterns to ensure all of your development efforts dovetail. Make sure you understand and assess your existing application landscape and pick a cloud architecture that meets your assessment.
  7. Dependencies. Third-party applications and data sources can gum up the works if you don’t have a coordinated program to deal with them. You must define dependencies and put in processes as a structural component of the migration effort to ensure success.

The DMI Advantage in Moving E-commerce to the Cloud

When your customer experience is on the line, you can’t afford unexpected glitches that chase people to the competition or projects that aren’t delivered on time and on budget. This reality underscores the inherent tradeoff of moving to the cloud: To get massive flexibility you have to deal with complexity and up-front cost.

At DMI, we have experts with direct experience in e-commerce operations across multiple retail sectors. We don’t tell clients what they need to do. We scrutinize their marketplace and current technology environment, and help them formulate a strategic, proactive approach to doing what’s best for their customers and their business.

It’s not easy to figure out. But it’s easier if you choose the right partner — one that is committed to the client’s success and knows how to successful navigate the unexpected pitfalls.

Andrew Powers, senior vice president, solutions delivery, digital commerce

How to Improve Your Call Center Today

How to Improve Your Call Center Today

It happens to every hospital or healthcare provider: A crisis or emergency erupts and suddenly patients are calling in droves with urgent questions — overwhelming your patient-care staff. You know this aggravates your patients and you want it fixed now.

You’ve probably heard about intelligent virtual assistants (IVAs), which use machine learning to automate a full range of activities in the patient support process. And you’re wondering: Can IVAs lighten the load on your call-center crews?

They can, but not soon enough to put today’s fire out. When you need help in time frames measured in days, not months, it’s best to think in terms of a journey to IVA, with small intermediate steps that lay the foundation for advanced automation a few months down the road.

While the initial phases do not put every fire out, they still provide priceless data about users’ habits. This data fuels intent-analysis processes that will help your IVA system make smart decisions down the road. Over time, user-intent signals will help you predict future patient support needs.

Thus, all of your patience and preparation early in the journey pay off all along the route. There’s no wasted effort.

These are three optimal phases for making the transition to IVA capability:

Phase 1: Add One Bot to Your Call Experience

It’s best to start with a single on-ramp in your journey to an automated patient experience. It could be a simple webchat bot that asks a patient one or two basic questions before forwarding the call to a human representative. This simple solution automatically eases the strain on your staff and doesn’t take long to implement.

Remember: Everything your patients do in this webchat bot will generate data that trains the IVA system to make smarter decisions as time passes. You can use any channel your patients prefer. The point is, you want to work the bugs out of the first automated process before moving on to more complex capabilities.

Phase 2. Automate Answers to Patient Questions

With your basic bot up and running, it’s time to add a few more on-ramps to your IVA journey.

That means using bots to answer more difficult questions and automate more of the patient support experience. You might also customize the responses depending on the channel — phones, email and text messaging, for instance.

Now, you have to focus more deeply on thorny issues like authentication: validating the identity of each person and remembering their favorite authentication methods.

Here, it becomes more important to train your support staff properly and confront any shortcomings in your backend IT systems. You need to make sure your legacy systems have enough power to process complex learning algorithms.

Again, you’re feeding data into your intent analysis process to ensure that each user can log in with their favorite methods in the future. Their questions and your automated answers will produce smarter bots, streamline the experience and improve patient satisfaction.

Phase 3. Implement an IVA System

Phase 1 and 2 gave you a firm foundation to implement an intelligent virtual assistant that can respond automatically to calls from a wide range of patients and tailor these responses to their unique preferences.

A full IVA system identifies callers and remembers their habits and behaviors on previous calls. Learning algorithms teach it to take on more complex challenges because it also folds in data from the rest of your patient calls.

The ultimate goal is to free up your patient-support staff to handle jobs that computers aren’t good at — like using their intuition and training to provide a savvy, humane response to a complex patient support issue. That helps improve job satisfaction, potentially reduce turnover costs.

The DMI Advantage in IVAs

DMI has an extensive track record with IVAs in multiple sectors like health care, finance and government. Our vast pool of talent in business consulting, automation, system architecture, machine learning, data science and patient experience ensures we have the right skills. Our focus on Agile methodologies gets the right solution into our clients’ hands in tight time frames. When you have big fires to put out, these are the skills you need.

–Niraj Patel, director, artificial intelligence

 

6 Things to Avoid in Your Headless Commerce Journey

6 Things to Avoid in Your Headless Commerce Journey

You can’t avoid every bump in the road to modernizing your e-commerce infrastructure. But you can anticipate the most common roadblocks, wrong turns and traffic jams.

E-commerce modernization usually means transitioning to a headless IT infrastructure. With headless, you decouple the frontend of your IT infrastructure — typically the presentation tier — from the backend, where most of the business logic resides. Headless lets you rapidly iterate your frontend to finetune your customer experience without having to coordinate everything with the backend, which would bog down development.

Avoiding these six pitfalls can make your journey to headless commerce go much more smoothly:

Strategic oversights. You can’t afford to scrimp on strategy in your headless commerce journey. That means starting with a discovery process and gap analysis that assesses your current IT state — systems, hardware, personnel, skills, partners and methodologies — and lays out a roadmap for moving toward a headless ecosystem that meets your current and future needs. The more planning you build into your strategic roadmap, the better your chances of success in the long haul.

Time-frame miscalculations. It’s easy to underestimate how much time is involved in a headless transformation. Every company has unique IT challenges and marketplace realities. You may have a small IT team that needs lots of help, or a large IT team that needs only highly specialized assistance. It takes a lot of fact-finding, research and meetings to figure everything out. That can take more time than you might expect.

Platform and software stack slipups. Missteps in choosing the right headless e-commerce platform or software stack for the head can cause headaches for years to come. Choose the platform that meets your current and future needs. Every software stack approach for building the head (presentation tier) has pros and cons. The best route is to draw up a list of requirements, assess your current IT skillsets and pick the software stack that gives you the most of what you need with the fewest compromises.

Skill misalignments. Conventional e-commerce platforms need abundant expertise in the backend, while developing the head on a headless commerce platform requires a separate set of frontend skills. Moreover, headless commerce requires a wealth of experience with cloud technologies and microservices. Your headless commerce journey must assess your skillsets across all the new technologies and plug any gaps you discover.

Methodology missteps. Headless commerce allows a rapid release and iteration cycle that requires continuous integration of skills from multiple disciplines beyond IT, such as UI design, digital marketing and product development. Agile and DevOps methodologies provide the framework for keeping everybody aligned during two- or three-week development cycles.

Botched buy-in.  Everybody must pull together. Otherwise, all the benefits of headless commerce collapse. That’s why it’s essential to secure buy-in from everybody involved in the transition — not only the leadership but also the rank-and-file technical teams and support people.

Picking a Partner for Your Commerce Modernization

Headless commerce delivers immense value in the digital marketplace, but you have to pay a cost in complexity to enjoy that value. To make it all work, you need a partner with deep experience in online commerce and broad technical expertise across frontend, backend and cloud software platforms. These are the capabilities that DMI brings to your headless commerce transition. Our consultants know how to merge commerce domain knowledge, IT infrastructure, marketing and user experience design to give our clients a head start in their headless transition.

—Atul Bhammar, senior vice president, solutions architect, digital commerce

How Headless Commerce and Magento Produce Amazing Shopping Experiences

This is the first in a three-part blog series about the use of Magento.

Headless commerce is changing the face of digital commerce because it allows companies to craft experiences that customers can’t get anywhere else.

A headless system decouples the frontend (typically the user interface layer) from the backend, where most of the computing power resides. This allows developers to customize user experiences for phones, PCs and other devices on the frontend while keeping a standard backend for the most demanding computing tasks.

Retailers are warming to headless commerce because it gives them a chance to set themselves apart in an era of relentless competition. Magento is an attractive option for headless commerce because it provides boundless flexibility to e-commerce system designers and managers.

On the front end. Magento allows frontend designers to leverage the powerful features of Adobe Experience Manager. Adobe has been building best-of-breed visual design software for decades. Adobe  Experience Manager has everything website and application designers need to craft seamless shopping experiences across multiple media platforms — smartphones, tablets, websites and more.

Before headless commerce came along, companies often had to choose an e-commerce platform on the strength of its backend computing power, regardless of any weaknesses in the frontend design system. There’s no more grin-and-bear it with headless computing. Designers can pick the best frontend tools for their specific needs. That leads to better experiences and happier customers.

In the middle. Magento has robust frameworks for the APIs (application programming interfaces) and PWAs (progressive web applications) that maximize the impact of headless commerce. APIs let multiple applications share data and communicate with each other (the GraphQL support added in version 2.3.x of Magento makes API communications more efficient). PWAs bring the functionality of a mobile app into a web page, providing app-like services without requiring users to download an app and update it themselves.

As customer experience developers implement more machine learning to customize and streamline online shopping, PWAs and APIs will become even more crucial to headless commerce.

On the backend. Rich consumer experiences powered by machine learning require substantial computing muscle. So, the same Magento flexibility that gives experience designers an edge also ensures that IT teams can implement the most powerful computing resources. Moreover, Magento’s advanced API frameworks ensure that retailers can plug their ecommerce systems into their systems for managing resources and customers.

While monolithic, all-in-one digital commerce systems are fading into history, Magento is leading the charge into the future because it helps developers get next-generation user experiences into the marketplace much faster. Bear in mind, however, that if your legacy backend system still performs to your satisfaction, you can keep it while leveraging all the frontend advantages of headless commerce.

A Quick Reality Check on Headless Commerce

The flexibility of headless commerce accelerates development timelines because you don’t have to align frontend development with your backend e-commerce computing infrastructure. But immense flexibility comes at a price: You have to invest time and energy in creating a well-thought-out roadmap to implement headless commerce.

That means taking extra care to account for variables like search engine optimization, bots masquerading as humans, proper analytics tracing and monitoring for errors that may no longer show up in traditional server application logs.

Magento has a global community of developers providing a galaxy of precise solutions to all manner of e-commerce challenges. With so many options available, a few stray missteps can undermine all your progress. At DMI, we draw on a deep well of experience in both the retail and the system development sides of the equation. We put these skills to use helping our clients craft an effective, efficient roadmap for implementing and managing Magento.

— Jon Wovchko, vice president operations & strategic consulting, digital commerce

Why it Pays to Transform Your Thinking about Data and Privacy

People need control over their data and transparency about how organizations use it. That’s the mindset companies must adopt in the new age of consumer privacy.

On the surface, it seems like a perfectly sensible, consumer-centered outlook. But the rise of anything-goes data gathering gave companies a lot of bad habits — lax security, opaque data policies, nettlesome behavioral tracking and sketchy third-party relationships.

That age is drawing to a close. Taking its place is an era where legislation like Europe’s General Data Protection Regulation (GDPR) and the California Consumer Protection Act (CCPA) is almost certain to proliferate in the years to come. Thanks to these new privacy rules, customers can discover how organizations use their data, forbid tracking of their online behavior and direct companies to delete or update the data in their servers.

Perhaps the toughest thing to get your mind around is that hundreds of pages of privacy legislation are actually excellent news. Though compliance is usually about as much fun as getting lost in a snowstorm, new privacy rules bring welcome clarity for companies using data to better understand their customers.

What’s more, you can take advantage of privacy rules to zero in on collecting the consumer data that drives the best outcomes. That’s a net gain over conventional data collection and analysis — if done correctly.

What We Missed in the Bad Old Days

The old way was to gather as much data from as many sources as possible, then use data science, analytics platforms, machine learning and other complex, expensive technologies to find the few grains of useful insight buried in a Gobi Desert of data.

It made sense in an era of easy access to consumer data. But it wasn’t exactly a sensible data strategy.

An effective data strategy starts with the information most directly relevant to your business. That is, you collect only the data that drives productive outcomes and advances your goals. This strategy is simpler and more cost-effective than hoovering up in everything, much of which is useless.

Getting Closer to Your Customers

In the new opt-in, permission-based world, you’re working with data from people who are interested in your product or service. Thus, the data they willingly share is inherently relevant to your objectives. Opt-in data is easier to segment for marketing purposes. It also gives you more specific, actionable information about the behavior of people using your applications and website pages.

Moreover, building online forms and folding them into a frontend data strategy is much easier to implement than developing massive back-end systems that require much more technical heavy lifting.

All of this can result in a more welcoming sense of intimacy in your customer experience. You can tailor offers to specific people and build more customization options based on the behavior of people who have agreed to engage with your organization.

Transforming Your Perspective on Privacy Isn’t Easy

Adopting a privacy-first data strategy requires a fundamental shift in perspective. Instead of gathering massive volumes of data on the backend, you’re crafting a robust data strategy on the frontend.

Making the transition successfully requires a convergence of skills in diverse disciplines, from SEO and email marketing to machine learning and system architecture. You also need a framework to persuade teams to adopt new methodologies and a roadmap for implementing the optimum technologies.

At DMI, we’ve developed powerful methodologies to help companies succeed in these kinds of transitions. We’ve learned from engagements with companies across every sector of the economy that managing change effectively is the bedrock of effective business transformation.

We believe that the current wave of privacy regulation represents an opportunity to develop data-rich, customer-centered websites, apps and marketing campaigns. The hitch is knowing how to make it work for your enterprise. That’s where our skills and experience pay off.

 — Michael Deittrick, senior vice president digital strategy, chief digital officer

Cracking the Code on Fan Engagement

In an age where consumers are in control, brands have to work harder than ever to cut through the noise to reach their consumers. Then they must also engage their audience in meaningful ways to earn their trust and loyalty. That means marketers are having to get creative. The brands that are willing to take a leap and do something bold are the ones that will reap the rewards.

When the International Spy Museum, a partner of DMI’s since 2014, was planning to move locations into a new, bigger, better, purpose-built facility across Washington, D.C., we knew we needed to do something big. The museum would be closed for more than four months for relocation, but this time was essential for generating buzz in advance of the grand opening.

Here are the four key principles we followed to build the wildly successful “Mission countdown” activation:

  1. Know Your Audience
    The first step in any marketing effort is to understand your audience. From owned data to surveys and customer interviews, knowing your consumer is essential. If you don’t know what their needs are, you can’t possibly deliver on them. If you don’t speak to them in the right way, or connect with them in the right place, they will quickly overlook you or worse, write you off entirely. Consider if you have an engaged fan base you can start with organically to validate your concept and get it off the ground, or will you need to build an audience from the start?

    For the Spy Museum, we had the benefit of four years of understanding their audience prior to the big move. We knew they had a core set of very loyal and very knowledgeable fans who followed the various Spy Museum social channels. We knew that if we wanted to connect with the fan base, we were going to need to speak their language. We had to create an experience that felt truly ‘insider’ and not like a marketing campaign.

    We decided to send our followers on their own undercover mission in the real world. Over the course of four weeks leading up to the opening of the museum, we released clues to 36 different dead drops hidden in the D.C. area that contained prizes from free museum tickets to access to the opening gala. To participate, fans had to crack clues to unlock the secret location of the dead drop, then go to that place to either collect the physical dead drop container or claim the digital dead drop pinned to that location. The technology we implemented enabled thousands of individuals to play at the same time while giving each their own unique experience, and allowing just 36 skilled agents to claim the prizes. The activation was a major hit with the Spy Museum fans, leading them to tag their friends to participate. It also generated a 28% increase in organic Twitter impressions month-over-month, as well as garnering earned media impressions to further build excitement and awareness for the museum.

  2. Be True to Your Mission
    Consumers are smart. They are skeptical of marketing. They only pay attention to the brands that truly connect with them, and they expect to be rewarded for their engagement and loyalty. So how do you earn the trust and attention of your audience?

    The key is authenticity.

    Don’t do a filmed stunt just because everybody else is doing it. Don’t post about an issue that is taking over social if your brand has no business being in that conversation. Start with your mission, and you can’t go wrong. Your brand is what it is, and if your marketing doesn’t represent that, the brand lift will be short-lived at best and tarnish your reputation at worst.

    For the Spy Museum, we could have done a simple ticket giveaway or social media contest. But none of that felt right for their brand. It took a tremendous amount of research and effort to create an experience that would surprise and delight the most knowledgeable spy enthusiasts. Each of the 36 dead drops was placed at a location where a moment in spy history occurred, like an actual dead-drop site, or a restaurant where clandestine meetings occurred.

    The 36 clues were all different puzzles, challenging our audience’s spy skills, like analyzing intel and cracking codes. This also enabled all players to engage, even after the prizes were claimed. The entire experience was carefully designed from start to finish to really put the audience into the shoes of a spy in the way that the new museum would upon opening. During a time the museum was closed, we actually turned the entire city into a museum where history came to life.

  3. Spread the Word
    It doesn’t matter how great your campaign is if nobody sees it. The rollout strategy is as important as the concept itself in creating a successful connection. You already know your audience from step one, now you need to meet them where they are. That may be your owned social channels, paid media placements or something else entirely.

    For the Spy Museum’s Mission, we released the clues in batches over the course of several weeks, giving more fans more opportunities to engage and win. We launched the game to the Museum’s followers first, giving our most loyal fans the first chance to win. Over the course of several weeks, we released more batches of clues and slowly began to use paid media to drive traffic. As the activation built momentum the earned press began, and as a result the final release of clues had the highest engagement of all the releases.

  4. Take Risks
    Fortune favors the bold. To get attention you need to do something exciting, new, fresh, even a little bit scary. Yes, the first time you do something it won’t be perfect. But consumers would rather you be exciting and not perfect than boring and expected, yet flawlessly executed.

In the case of the Spy Museum activation, we built an experience like nothing that had ever been done before using a technology platform that was new to the market. While we did everything we could to ensure success, there was still an element of uncertainty. But with great risk comes great reward. All 36 prizes were claimed. Most of them were claimed within just a few hours of the clues being released, one prize took just 23 minutes to be claimed. Thousands of existing fans were engaged, and thousands more became fans. Earned, owned and paid media generated more than 2 million impressions. Most importantly, the museum delivered an authentic experience and delivered on its mission to educate, even when their doors weren’t yet opened.

— Elizabeth Van Blargan, associate creative director, DMI’s Brand Marketing & Customer Experience Division

Why Blockchain May Prove Essential to GDPR Compliance

Blockchain may turn out to be the killer app for GDPR compliance in the 2020s.

How so? Well, blockchain creates a secure way to track the provenance of digital transactions. That aligns well with the demands of GDPR, the European Union’s General Data Protection Regulation, which requires companies to develop vigorous data-protection frameworks.

GDPR governs the digital privacy rights of everybody living in the EU. Companies outside the EU have to comply with GDPR if any of their digital transactions collect data about EU residents. That makes pretty much every website publisher and e-commerce site subject to GDPR rules.

GDPR compliance poses three primary challenges to companies:

  • Understanding who has access to people’s data. Within your company, you need to ensure that nobody can misuse personal data. Moreover, you must be compliant in any situation.
  • Staying transparent on your data policies. You have to tell users how their data is used and how they can help keep their data private.
  • Understanding where your data is going. You must document the paths data will take after you’ve collected it. If people’s data goes to third parties, you must be able to track it accurately.

Blockchain’s distributed-ledger architecture helps with all three of these GDPR requirements. It starts by encrypting an initial entry on a digital ledger. That data point cannot be erased or altered. Rather, any changes are added to the ledger and must be approved by everybody sharing it. This makes it extremely difficult to create fraudulent or fake entries.

All data has to be stored, transmitted and kept secure. Blockchain can be used to build an encrypted data trail so you always have a complete understanding of data storage, access and transmission. Moreover, you can increase transparency and build trust because you have a mechanism to keep your promise to protect users’ data.
It’s true that blockchain has generated more hype than results in recent years, but that’s often the case with promising new technologies. Inflated short-term expectations lead to discontent that obscures the long-term potential.

Sure, there’s a lot to work out. Blockchain is a sophisticated technology and GDPR is a complicated regulatory regimen. For all the uncertainties, one thing seems certain: GDPR and similar data-protection rules will grow more pervasive in the 2020s. And organizations will need all the help they can get to avoid fines and adopt transparent data policies.

At DMI, we’ll be looking for ways to converge the data-policy needs of clients, customers and regulators. If blockchain looks like the optimum GDPR solution for our clients, we’ll be putting it to work.

-Varun Ganapathy, director/digital technology office UK/Europe

Digital Twins: Mining the Potential of Real-Time Modeling

The appeal of a digital twin is obvious: You deploy a digital model that mimics real-world behavior — detecting inefficiencies, optimizing performance and learning to improve in real time.

Digital twins are starting to generate buzz in the tech sector because they represent the next phase in the evolution of computer modeling. Conventional digital models attempt to predict future results before building complex systems, anticipating problems in the virtual realm before they cause expensive trouble in real life. Digital twins build on these strengths by providing instant feedback and machine learning.

Fortunately, the sensors, networks, software and computers required to build digital twins are readily available. Indeed, they’re already finding a home in Industry 4.0 applications, where they’re streamlining production and enabling predictive maintenance.

Moreover, there are strong incentives to move these interactive replicas into new realms. After all, if digital twins can optimize machines, why can’t they improve human outcomes?

That’s where things get complicated.

Consider a sophisticated digital twin used by a professional sports team. It’s conceivable that wireless sensors in clothing and equipment combined with digital video cameras, 3D modeling and advanced learning algorithms could mimic an entire game while it’s being played. Sensors and software could detect which players are off their games and recommend improvements in real time.

This futuristic scenario is easy to envision. Embracing the full potential of digital twinning, however, is a lot more challenging.

Where to Start With Digital Twins

Pretty much any behavior in the natural world is a candidate for digital twin development. It’s not just people and machines. It could be weather, the flow of water or the accumulation of pollutants.

Thus, you’re looking at a veritable mountain of distractions and dead ends. To mine the nugget of productive opportunity with digital twins, you have to narrow your focus.

To do that, ask some basic questions: Do you have a process where you’re reasonably certain that a better understanding of customer behavior will improve revenues or profitability? Do you sell a complex product with a steep learning curve that would benefit from insights on user behavior?

Zero in on a few processes you’d like to optimize and build from there. Remember, machine learning is a core component of a productive digital twin. If you build it right, it will teach itself to work better over time.

It’s imperative to avoid bright-shiny-object syndrome. You have to start with a pressing need — not a nice-to-have.

4 Mandatory Skills for Digital Twin Development

After you’ve targeted your best digital-twin opportunity, you have to amass the skills required to make it happen. These skills span four disciplines:

  • Psychology. Like a designer of user interfaces or customer experiences, your digital twin must reflect and respond to cognitive processes that drive human behavior.
  • Physiology. A digital twin must account for the subtle interplay of nerves, muscle and bone during the use of a device or software application.
  • Architecture. System design drives the effectiveness of a digital twin. Your model must optimize the interactions of networks, sensors and learning algorithms.
  • Engineering. Computation combines statistical analysis with the logic of artificial intelligence and machine learning. Savvy engineering supplies the accuracy and relevance that produce success with digital twins.

Your digital twin solution will need equal measures of design creativity, strategic vision and technical acumen. Dovetailing all these skills is a non-trivial task.

Embracing the Future of Digital Twins

Admittedly, digital twin technology is in its infancy. In the years to come, innovations in edge computing and the growth of 5G wireless networks should expand its horizons. Advances in artificial intelligence, machine learning and neural networks will open even more opportunities.

Even if you don’t think digital twins are a good fit for your business today, it’s a good idea to monitor developments — especially in the consumer sector. If a breakout innovation hits the mass market, it could be as big as the smartphone.

We’re not predicting the future at DMI, but we do know promising technology when we see it. As we gather more insight and experience designing and implementing digital twins, we’ll make sure our clients benefit from everything we learn.

–Michael Deittrick, senior vice president digital strategy, chief digital officer

DMI Digital Leader Award – Alex Spinelli, LivePerson

DMI Digital Leader Award - Alex Spinelli, LivePerson

Creating AI-Powered Conversational Interfaces for the World’s Largest Brands

Tell us about the LivePerson mission.

Our mission is to make life easier for people and brands though trusted conversational AI. Leveraging decades of data and a powerful AI-engine, we develop conversational experiences for top companies including HSBC, Home Depot, Orange, and GM Financial, helping to ensure today’s consumers are served with the personalized customer experience they have come to expect.

Explain the “Fourth Industrial Revolution.”

The term “Fourth Industrial Revolution” represents the blurring of boundaries between the physical, digital and biological worlds. We are at the start of a convergence of advances in artificial intelligence (AI), robotics, the Internet of Things (IoT), 3D printing, genetic engineering, quantum computing and other emerging technologies. This convergence is the force behind many products and services that are quickly becoming indispensable to modern life, GPS for example. This is also paving the way for a seismic shift in the way people live day-to-day and the way business is conducted. We at LivePerson are excited to be helping to manage this change on behalf of our customers.

How is the “Fourth Industrial Revolution” affecting consumer behavior?

Differentiation based on brand is rapidly disappearing. As technology has enabled businesses to offer more connected experiences, today’s consumers have many more options and are not afraid to switch brands to find a better experience. In fact, 73 percent of consumers will give up on a brand if they cannot get an answer to their question within 10 minutes. Consumers have come to expect immediacy when it comes to brand engagement.

What percentage of consumer inquiries can be automated?

Nearly 70% of consumer inquires can be automated. What’s more, 90% of consumers begin their shopping journey online but in the U.S., less than 15% of sales are completed online. Consumers need to ask questions, get advice and understand their options before making their purchases. Conversational interfaces make this possible without the shopper ever having to visit a store or place a call. Today, 50 percent of all conversations (tens of millions) on our platform are automated; that’s a jump of almost 200 percent over past year-and-a-half!

How difficult is it for companies to implement conversational interfaces?

Building automations can be slow and fragmented with a heavy reliance on developers. However, our Conversation Builder is an all-in-one platform tailor-made for conversational commerce, giving brands a dramatically faster and non-technical way to implement automation. Additionally, team members, such as customer care managers and even qualified agents, can participate in creating and optimizing chatbots.

What role does messaging play in the future of commerce?

Today 13 million texts are sent every minute in the world. There are 100 million messages sent every day on platforms like WhatsApp and Facebook messenger. That’s astounding. Thus, many of the tasks we now do, such as shopping, will be shifted to messaging and voice platforms such as WhatsApp, Apple Business Chat, and Alexa. Conversation is just a much more natural way to interact with brands. For businesses to scale this, they’ll need the help of really effective conversational AI, which is where we come in.

What has your experience been like working with the DMI team?

We at LivePerson have been extremely pleased with the DMI partnership. The team’s technical expertise is impressive and we share a common vision and passion for digital transformation. Additionally, with DMI’s deep roots in the government contracting sector, we look forward to exploring opportunities to enhance the customer experience for U.S. federal agencies and the Americans they serve.

NRF2020: They Don’t Call it The Big Show for Nothing

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My Impressions of the 15th NRF Expo and Show

As a technology professional focused on retail and commerce, this was my 15th NRF Expo and Show (but who is counting?). The venue is, of course, enormous, yet convenient. The content is breathtaking and well …breathtaking. The experience can be a bit like drinking from the proverbial fire hose. At certain times over the years, it was difficult to differentiate between an actual positive technology trend or just hoopla.

I have been here before to hear about everything from RFIDs, a new company named Amazon that was suddenly selling more than just books and CDs (remember those?), self-checkouts and the promise of kiosks, and of course, the “elusive” predictive merchandise and financial planning solution everybody seems to always be looking for. Here’s what REALLY impressed me this time around:

  1. AI is King. There were innumerable presentations of a vast number of “solutions” to predict, discover, deploy and “learn” from omnichannel customer transactions. Everybody was speaking of these as a “turnkey” solution that can produce immediate results. What gives? The best approach here is to match your AI strategy with a solid data cleansing and prioritization strategy. Trust me, you can’t have AI with bad data. The best solutions I saw incorporate AI to cleanse your data and then AI to decipher, understand and suggest actions based on that clean data.
  2. Customer Experience is Queen. So, you have clean data, you say? And a good AI engine to crunch it and learn from it? Well, now you need a frictionless experience for your customers. As some of my CX friends say, the journey is the experience and the customer is the journey. In other words, customers leave when they have a bad experience and they do not come back. However, when EVERY customer interaction is the result of thoughtful analysis, focused market testing, geocentric pricing elasticity, and is supported by a, “we are here for you at any time and in any channel you choose to interact with us,” you are way ahead of the herd.
  3. Game of Thrones. Well, the King and the Queen reign together. Companies that are successful in acquiring customers in current markets either by coming up with new (and more qualified) customer segments and the companies that are growing in new markets do the following: They are using AI and CX to their advantage. What exactly do I mean? Well, let’s say that you know that a high percentage of your customers use a messaging app (let’s say Whatsap), and you also know your customer care experience is not world class, and in fact, is costing you way too much. How would you address both issues? At DMI, we would strongly suggest that you look into Conversational Commerce. Chatbots are smart, fast and adaptable. They can enhance the customer experience by allowing your customer to communicate in the medium of their preference. Instead of calling to check on their order, they can text your customer care organization. Instead of downloading an app, or going to a brows