But the good news is, you have a solution!

The answer is hyper-automation. This technology enables enterprises to delight their customers with an interactive, immersive, and personalized experience.

What is hyper-automation?

Hyper-automation is the planned application of a wide range of tools, platforms, and technologies, including Artificial Intelligence (AI), Machine Learning (ML), Intelligent Document Processing (IDP), Robotic Process Automation (RPA), etc., to expedite operations and improve their effectiveness. It enhances business processes and integrates functional and process siloes.

Benefits of hyper-automation in the hospitality industry

Streamlined Reservation Procedure: Every customer wants a simple and quick booking procedure, especially in the travel industry. At the same time, customers also look for discounts on different portals and book the hotel that offers the best deal. Additionally, when there is a mass cancellation ( it happened during the pandemic years) making a refund to each customer was a huge task All these together have made hotel reservations a cumbersome process for hotel owners.

All manual repetitious operations, such as bookings and cancellations, can be automated with rule-based configuration and intelligence-based automation. Additionally, the technology enables instant refunds following cancellation.

Improved management of hotel tasks: When you go to a hotel and place your first order, the staff who takes your order is the first touch point where a brand impression is created. The first interaction can make or break the reputation of the hotel.

But a hotel owner can completely mitigate this risk by leveraging a hotel job management system.

For example, if a wrong staff member is given a task, they only need to immediately enter the information into their task management software on a handheld device. A prompt response will result from the automated rules and alerts notifying the affected party or department.

Contactless and simple check-in and check-out: The COVID-19 pandemic has created a demand for contact-free services. Customers can check into their rooms by simply arriving at the hotel using their smartphones thanks to automatic check-in software. This means the customer doesn’t need to wait at the reception to get their room keys. Additionally, it enables the hotels to clear the headspace for their staff and lowers the operational cost.

Respond in a timely manner to consumer queries: Nine out of ten times, customers who call or send an email with a question must wait for sometime to hear back. Longer wait times can negatively impact a customer experience.

The use of chatbots and voice bots have evolved as a crucial channel of communication for the hospitality sector. If a customer’s question can be answered right away, the system processes their emails and chat requests, analyses them, and responds appropriately. If not, the Chatbots/voice assistants forward the inquiries to a live agent, who is now free because there are fewer demands for answers.

Improvements in Customer Feedback Management: When consumers have a negative experience with a brand, they typically write online reviews about it. There are considerable chances that you might lose a sale if there are many negative reviews or if they are not addressed right away. This can be detrimental to your online reputation.

A hotel task management system comes with a built-in automated feedback management system. The customer support team is automatically notified whenever there is a negative review to take appropriate measures.

Are you ready to embrace hyper-automation technology?

Hyper-automation is the future of the hospitality business. It enables business owners to fully refocus their attention from mundane data-oriented duties to more crucial functions that enable them to provide superior customer service.

Author:
Vitesh Kohli is an Intelligent Automation thought & execution leader with a track record of setting up CoE, best practices, robot delivery, managing change and extensive program and project management experience with a strong entrepreneurial background. Have strong expertise in leading Transformation -Intelligent Automation across industries. Strong knowledge of planning big robotics set-ups, cognitive-based chat products, multi-components automation and multi-product Tech solutions. He is a domain Expert and Hands-on Technologist using Artificial Intelligence, Intelligent Automation and Conversational Commerce to solve business problems in large enterprises.

Source: Gartner

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What is post-sales support?

Post-sales support or after-sales service is a service that you offer after a customer has purchased a product. Anyone who sells a product can offer after-sales support — be a retailer, manufacturer, or service provider. Usually, after-sales service includes support regarding product warranty, usage, repair, or upgrades. Post-sales support is as important as the product itself and can make or break your business. For some customers, after-sales service can be a crucial factor influencing their buying decision.

Benefits of post-sales support:

Assisting organizations in maintaining high customer retention rates is the fundamental motivation behind after-sales service. It ensures customers get as much value as possible from their purchases. A great after-sales support program can help you build brand loyalty. And when your customers become happy, they become your repeat customers! Not just that, they become the biggest brand ambassadors recommending your product through word of mouth, bringing you more sales.

Challenges of post-sales service:

Serving multiple customers simultaneously: Managing various customers simultaneously (during peak hours) is a crucial challenge. Companies must keep a buffer and pay overtime to their resources to manage the extra workload.

Slow response time: Hold time can be due to numerous reasons, be it new hires, complex processes, or frequent process updates, but no one likes the hold time; we all know that.

Limited support window: Due to budget limitations, many small or medium size businesses offer after-sales support in specific time windows. Customers who need help beyond that time window may feel frustrated, especially when they have an urgent requirement.

Inexperienced customer service: Because of high attrition, there are constantly fewer experienced resources in the team. New hires lack in-depth process knowledge, so the First Call Resolution (FCR) rate is low, and the hold time is high.

Call transfers: Every time a call is transferred to another agent or supervisor, the customer has to repeat the issue/requirement. When a customer has urgency, it makes the situation worse.

Role of BOTS in streamlining post-sales support:

24×7 support: An order tracking bot provides all order delivery details to the customers at once. The chat widget prompts the customer to ask, “where is my order?” Or “I want to know my order status?” This bot works 24/7 and automatically responds to the most frequently asked customer queries about order delivery with high accuracy.  

Warranty Support: This is possibly the most common after-sales service companies provide for almost every product. Warranty services include repairing and replacing the products the customers bought for a selected period. For example, BestBuy in the USA offers multiple warranties and tech support membership offers along with the products. Customers may have different queries related to its coverage, option of extending the warranty, warranty term, etc. A bot can respond to customer queries related to the warranty of the products sold by the retailer easily.

Installation Support: Though most products come with an installation manual, customers may still have installation queries and need support. A bot can easily handle simple questions, while complex queries can be transferred to human agents during the conversation.

Product Features / FAQs: A bot comes in handy to answer any product feature-related queries. It can also integrate with OEM applications to pull updated details. For example, a customer may ask how many Android updates the mobile phone is eligible for that they have purchased.

Technical Support: Most retailers dealing in software-based/IoT devices (think CCTV cameras) have to keep a team that provides technical support for the products sold by the company. Customers connect with the technical support team for any product issue, which understands the problem, opens the tickets, and directs it to the relevant department. A bot can do this job without any breaks. It asks the appropriate queries to the customer and, based on the response, decides the issue type and offers a further course of action. Accordingly, it registers the customer’s request and forwards it to the right team. The customer receives information such as the time to resolve the issue, the following steps, etc. The customer always has the option to ask further queries, or talk to an agent anytime during the conversation with the bot.

Product Return / Replacement: Though retailers provide streamlined solutions for any return or replacement, there can still be exceptions, and due to that, customers have to do follow-ups, raise complaints, or have simple queries. This requires the companies to have support executives to manage such scenarios. A bot can handle this situation independently and efficiently by accessing all the details related to customer data and all possible solutions. Apart from this, there are other areas where the bot can help engage with the customers, such as upgrades, exchanges, offers, etc.

Conclusion:

Today, no one likes to be on lengthy support calls, pressing the IVR keys, waiting for a live chat agent to respond, and waiting endlessly in the ques. The voice bots/chatbots facilitate seamless live communication and provide customer support 24/7. Bots help companies save time and money, offer a smoother customer journey, reduce consumer stress, and help grow your business.

At IGT Solutions, we have implemented multiple chatbot and voice bot solutions to help our customers optimize their costs, improve customer satisfaction, and provide round-the-clock support.

Author:

Manish Arora is Manager Consulting at IGT Solutions’ Intelligent Automation and Conversational Bots Practice. He is an Automation expert with 14+ years of experience across Travel, Telecom, BFSI and Retail domain. With a strong background of Digital Transformation and Hyperautomation, Manish has extensively worked on elevating clients’ experience by helping them at various stages in their Automation journey. He can be reached at manish.arora@igtsolutions.azurewebsites.net

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What is Computer Vision and what is CX?

Computer vision is an AI capability that allows IT solutions to extract data from digital images, videos, and other visual inputs, understand it and take or recommend action. It uses cutting-edge ML and AI capability to replace the human eye.

As per Annette Franz, founder, and CEO of CX Journey, “Customer experience is the sum of all the interactions that a customer has with an organization over the life of the relationship with that company or with that brand”

Why is Computer Vision enabled CX important?

As consumers are increasingly embracing digital, many of their transactions and interactions are getting digitalized and personalized. Computer Vision is one of the technologies that enable this personalization, and the possibilities are immense.

What are some of the use cases of improving CX through Computer Vision?

The most common use cases these days are in the retail and fashion industry.

Effective CX in a retail store nowadays depends on hassle-free availability, quick checkouts, and customized offers. This may seem to be difficult to achieve especially during periods of high footfall. Retail Stores can use Computer Vision for quick self-checkout, automatic refilling alerts for empty shelves, monitor customer activity for suspicious behavior, measure footfalls, and do customer traffic management in real-time.

It can reduce waiting time in long shopping checkout queues by automatically alerting the activation of more checkout nodes seamlessly. It can also provide accurate footfall analytics with data on repeat customers in the store etc.

The Fashion Industry is leveraging Computer Vision to create image-based searches for design availability, virtual trial rooms for e-commerce to give a look and feel or to generate new ideas and provide intelligent recommendations. Similarly, it can also be used for the furniture, home décor, and eyewear industry to name a few.

Parking management in large shopping malls can be another use case. Computer Vision can be used for occupancy detection and management based on visual data inputs. Hassle-free parking will optimize the shopping traffic and improve the CX of customers shopping there. This can be extended to many other applications of parking management such as – at airports, public transport parking, or large trade shows or concerts.

 How can you apply Computer Vision to improve the CX of customer support?

Customers need a quick and effective resolution of their needs when they connect with a support center. The optimal CX here would mean minimal waiting times and minimal steps in an effective resolution process.

Customer Care centers can be upgraded with Computer Vision enabled Virtual Assistants. It can extract details, authenticate customers and automatically fill details based on visual data inputs of the customer or the product. It can zero in on objects in stills or videos provided by customers and recognize details like category, model no., and manufacturer.

Advanced solutions also have the capability of detecting the operational status of components of a device and detecting faults with high accuracy even for poor-quality images provided by customers.

 How can you apply Computer Vision to improve the CX of air travel industry?

Air travel passengers choose an airline based on the CX offered, besides cost and convenience. Computer Vision can help provide a better CX with intelligent baggage handling, quick check-ins, advanced airport security capability, better aircraft traffic management with the least delays, real-time snag detection of aircraft and in the airport infrastructure. It can also pull up details of repeat passengers for in-flight staff for a better and more customized flight experience. A customer would be delighted with the more customized, hassle-free, delightful, and on-time experience.

Do you think the time has come for Computer Vision to transform CX across domains?

The applications of computer vision are endless and can be used at every node of customer interaction that involves vision to create a better customer experience. It generates a large amount of accurate data for optimization of the experience with analysis and insights in real-time. Businesses that care for their customers want to provide a high customer experience that CX enabled with Computer Vision can provide.

Computer Vision-enabled CX is happening now!

Author:

Nitin Rai is the Vice President of Marketing and Growth Initiatives at IGT Solutions. He has spent over two decades working with leading information technology service providers and is currently enabling various aspects of Marketing, Demand Generation, CX, Digital, MarTech deployment, PR, and Communications at IGT Solutions. He aims to help the organization attain an enviable position as a leading Digital CX, Data, and Digital services provider in the chosen industries, globally.

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Let’s start with some industry examples where companies across the world have been working with legacy systems as they are critical to their business.

• Mainframe systems that airline companies use for reservations and ticketing systems
• Command-line interface systems based underwriting engine used by insurance companies
• Companies with a core platform on legacy systems (such as COBOL, DB2, etc.) and being used by numerous customers

Many companies are generating good revenues from their operations and supporting the business, but they are missing out on the opportunities for connected data across the ecosystem. The architecture is not supported for enabling seamless data porting, scalability, and speed. Moreover, these systems have a higher cost of operation and high maintenance; and are plagued with usability and security issues. Technological obsolescence and resource scarcity are a few more challenges.

Key challenges with the Legacy systems

Integration issues with other systems: Gone are the days of monolithic architecture; nowadays, solutions are designed to have benefited from multiple systems connected via APIs. Modular and SOA-based architecture are common with scalability benefits and integration with other 3rd party systems. Legacy systems are not designed to integrate with other heterogeneous systems and thus cannot achieve fully integrated systems.

Go to market is slower: Legacy systems usually follow the waterfall model of software delivery, and aligning with the market demand of releasing software features on the fly is not feasible.
These systems are heavily focused on a manual way of working with little or no integrations available for 3rd party build, configuration, and CI/CD tools, causing the entire process to become slow and error-prone.

Misalignment with customer requirements: In the current era of a customer being the king, legacy systems are not synchronized with customers’ needs, especially in terms of flexibility, agility, usability, and customer experience. Legacy systems are still tightly coupled with OS, interface, screen, etc. In the case of growth, these systems cannot scale at the same pace as that of business.

Artificial Intelligence and machine learning: Legacy systems are not built to integrate 3rd party data sources and are relatively inflexible. When the world moves towards NoSQL, a flat-file kind of database, legacy systems still run on relational DBMS, slowing the entire operation. Creating intelligent dashboards analytics is a cumbersome task, if not impossible, in these systems. These systems cannot harness the power of AI/ML and achieve predictability and digital transformation benefits.

Human resource challenges: The availability of skilled resources with expertise in legacy systems is seeing a decreasing trend. Universities and institutions, nowadays, focus more on newer technologies such as cloud, AI/ML, Internet of Things, Intelligent Automation, Blockchain, DevOps, etc. This means the engine to produce the team with legacy application skills is dying; moreover, the new generation of engineers is inclined to work on the latest technologies and not on legacy ones.

Compliance and Regulatory requirements: Nowadays, regulatory authorities and governments are very keen on adhering to compliances or heavy penalty is imposed on them. HIPPA, SOX, PCI, GDPR, etc., require your technology to be current and aligned with the regulations. These rules demand specific data to be shared with government bodies, and their implementations/modifications are very time-consuming in legacy systems.

Solutions to legacy technology challenges

We understand the challenges legacy technologies pose, like speed bumps, to leverage data modernization and use it to achieve higher revenue and innovative offerings at the utmost speed to enhance customer experience.

The question is, how can we resolve these legacy issues?

Digital transformation is the key to reducing the risk and unpredictability and improving the customer experience in the current market.
The implementation of Agile and DevOps coupled with a technological revolution comprises cloud, IoT, and AI/ML with enriched and interconnected data that will resolve the issues mentioned above.
Each organization is unique in the context of a market, customers, products, ecosystem, etc., so there can’t be an umbrella approach. The approach must be customized to different companies to harness the full benefits of digital transformation.

How can IGT Solutions help you?

With its technological expertise and process champions, IGT Solutions is well placed to implement methodologies and achieve a faster delivery cycle, cost optimization, and excellent customer experience.
IGT’s expertise in transitioning from legacy to cutting-edge technologies in a phased manner does not disrupt the ongoing business engagements. It can easily transition into the latest technologies fitting to customers’ needs. IGT’s expertise in Agile, DevOps, Cloud, and experience in implementing AI/ML, IoT, and Blockchain will help you ensure a smooth journey from legacy to latest technologies.

Author:

Yatender has 20+ years of experience in software test engineering. As the head of Testing Practice at IGT Solutions, Yatender is actively involved in innovations related to test engineering covering new tools, technologies, and solutions, and enabling IGT’s clients to achieve faster time to market quality improvement, and optimization of developer efforts in overall SDLC. A result-oriented leader, proficient in delivering high customer value and achieving excellence in service delivery management with proven skills in consulting and managing large and complex test programs. When away from work, he enjoys reading on a variety of topics and spending time with kids.

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Gartner defines Customer Experience (CX) as “the customer’s perceptions and related feelings caused by the one-off and cumulative effect of interactions with a supplier’s employees, systems, channels or products.”

Acquiring new customers is essential, but at the same time, organizations should prioritize improving their existing customer base by providing them with excellent customer experiences, leading to higher revenue and profitability.

Need for Comprehensive Customer Experience Assurance Platform

Customer Experience Assurance is a platform to provide correct feedback to the stakeholders on customer experience (CX) areas at various product lifecycle stages, enabling teams to make informed decisions on CX and continuously improve it.

Several organizations already have done or are in the process of creating a Customer Experience Assurance service as a standalone unit or as part of their customer experience team. This is helping them enable end-to-end automated customer experience monitoring and assurance for various processes.

CX assurance platform is a catalyst to provide deep insights into the customer experience with the help of quantitative and qualitative analysis based upon real-time data on customer behaviour. A typical CX assurance platform will consist of an ecosystem of assurance on areas such as usability, accessibility, availability, performance, compatibility, and service assurance.

Challenges in measuring Customer Experience

Many organizations have their own CX measurement, and improvement initiatives are being implemented in siloes without interfacing with different departments or validating back with their end customers, causing low ROI on CX efforts. There is also an empathy vacuum for customers, leading to higher customer churn.

Solution approach for Digital CX Assurance Challenges:

Understanding Your Customers: It is important to understand your customer to fine-tune your customer experience strategy.

Gartner provides the below framework to Understand Your Customers Better.

Identify Digital Customer Experience KPIs: To enhance customer experience specific to the company’s product, we have to first identify and measure KPIs and then work to improve CX.

In one of the surveys, the top KPIs being tracked for measuring customer experience are depicted below:

• Customer satisfaction score
• Product or service quality metrics
• Employee engagement
• On-time delivery
• Repeat order
• Returns rates
• Customer efforts score
• First call resolution rate
• Willing to be a reference customer
• Churn rates

Each organization can have customizations as per its maturity, resources and long-term business goals.

Digital CX Dashboard: Gartner recommends the below framework for the CX metrics dashboard.

Enhancing Customer Experience for Higher Revenue and Profitability: There are four primary categories of customers’ salient experiences, namely:

• Interaction Experience –These are the evaluations customer makes based on their interaction with an organization.
• Product Experience – Customer Experiences post product/services usage.
• Brand Perception – Customer’s perception towards a brand and how the brand is delivering value to them.
• Price – Customer’s view on the value received in the price paid to the product

Though all these four areas are important to provide a great customer experience, Continued improvements in the product experience are rewarded with greater loyalty.

Every organization must continuously work to improve customer experience on all the factors described above to retain the existing customer, increase customer loyalty and stay ahead of the competition.

Benefits of Customer Experience Assurance solution

The CX assurance platform has helped organizations keep a tab on CX metrics and fine-tune their strategies to improve customer experience. The following areas have been found to improve with meticulously designed customer experience assurance solutions:

• Real-time insights on CX metrics
• Improvement in customer lifetime value
• Journey mapping and orchestration
• Higher customer loyalty
• Greater operational efficiencies and higher profitability

Conclusion

IGT Solutions is well placed to deliver a customer experience assurance platform to enable organizations on providing hyper-personalization, sentiment analysis, and trends in CX changes coupled with real-time intelligent data analytics.

Author:

Yatender has 20+ years of experience in software test engineering. As the head of Testing Practice at IGT Solutions, Yatender is actively involved in innovations related to test engineering covering new tools, technologies, and solutions, and enabling IGT’s clients to achieve faster time to market quality improvement, and optimization of developer efforts in overall SDLC. A result-oriented leader, proficient in delivering high customer value and achieving excellence in service delivery management with proven skills in consulting and managing large and complex test programs. When away from work, he enjoys reading on a variety of topics and spending time with kids.

The post Digital Customer Experience Assurance appeared first on IGT Solutions.

The Business Intelligence analysis technology has been present since the 1980s when the ‘Gen One’ BI was first introduced in the market. It could generate business reports but heavily relied on IT professionals and was inaccessible to those with no IT background. However, the reports generated by ‘Gen One’ BI were beneficial for enterprises, and hence it sparked the interest of many business analysts.

A few years later, the ‘Gen two’ BI was introduced as an updated version of its predecessor. The second-generation BI made the data more accessible and consumable to business owners. Overall, the ‘Gen two’ BI made the analytical tasks easier for businesses, but there were still many flaws when used for Big Data Analysis. According to a report by Business Wire, the adoption of Big Data is still an issue for 73.4% of enterprises. Another problem with the ‘Gen two’ BI was its high cost and time-intensive nature.

To solve these problems, a couple of years ago, the third generation of BI, which is commonly referred to as ‘Next-gen BI’, was introduced, and its prospects reflect the visions of CXOs across the world. The ‘Next-gen BI’ utilized Artificial Intelligence (AI) for providing real-time insights and predictive analytics from Big Data through visualization.

As the third generation of Business Intelligence came into the picture, many enterprises have been adopting it. As of 2021, the BI software segment is expected to generate a revenue of 22,845.99 million U.S dollars.

The following article will discuss different aspects of Next gen-BI, like how data visualization is done in BI, how it can add value to businesses, and many more.

How Is Data Visualized In BI?

Data visualization is a process of presenting raw data in eye-catching and graphical formats such as bar graphs, pie charts, bar graphs, etc. The purpose of visualization is to recognize trends and patterns among the different units.  Traditionally it was done manually on software like Microsoft PowerPoint, excel sheets, and photo-shops.

The modern and more efficient way of doing visualization is by using BI tools. But before we can see the visualization of the data, there is a long process involved that raw data has to go through.

Here is how visualization is done in BI,

• Initially, the types of data and data sources that are going to be visualized are defined.
• After the first step, the transformation methods and database qualities are identified.
• Then, the data is sourced by BI from its initial stages. Here the data is cleansed, mapped, and standardized to a unified format.
• With the help of APIs, data is moved to the staging area.
• The cleaned data is finally moved into the storage, and this data is then visualized.

What Can The Next-gen BI Offer To Businesses?
There are numerous benefits that organizations can gain by opting for Next-gen BI. All the tedious and repetitive tasks can be automated with Next-gen BI. It can help businesses to perform better because of its following capabilities:

Data Is More Accessible, And The User Interface Is Intuitive: According to Dataversity, the customs data visualization offered by the next-gen BI has significantly upgraded the outcomes of BI. By opting for Next-gen BI, many steps in the enterprise workflow can be automated, improving the overall efficiency of the workflow.

The automation of processes allows employees to focus more on their primary tasks rather than looking into data for hours every day for insights. This reduces the friction throughout the entire data lifecycle.

Next-gen BI has allowed businesses and customers to access data from their fingertips. Nowadays, there are AI chatbots created especially to answer all the data-related queries. These bots analyze the data and put forward the best visual representation for the users.

It means that companies now don’t have to invest their time creating pie charts or bar graphs anymore.  Anybody can generate relevant information in a matter of seconds just by asking some set of questions.

This is a considerable improvement in the data analysis field as earlier businesses required human resources to extract, analyze, and visually represent the data. With the constant development of technology, next-gen BI is no longer just a tool for companies, and it has become more conversational and intuitive.

Real-time insights: In today’s world, companies need to act on real-time data. The next-gen BI provides real-time numbers that enable businesses to analyze live data and gain real-time insights. A report by Forrester shows that insight-driven companies are growing at the rate of 30% per year.

The Next-gen BI is incorporated with Artificial Intelligence (AI) and Machine Learning (ML) technologies. ML algorithm makes next-gen BI a self-learner and allows it to learn which insights are helpful for the business making the presented data more refined without any human feedback. AI assists it in automating the process and producing actionable valuable real-time insights in an increasingly timely manner.

Better Predictive Analytics: As Next-gen BI performs Big Data Analysis, it can offer predictive analytics. Predictive analytics enables top executives to lay out a plan of action for their business’s further development and expansion.

Assist Companies To Make Better Decisions: Another way the ‘Next-gen BI’ adds value to the business is by allowing them to make better decisions through its insights and hence decreasing the risk factor. According to TechCrunch, a company with the help of next-gen BI software witnessed an increase of $100,000 revenue per year.

The ‘Next-gen BI’ also offers insights into customers’ behavior, which can also assist in delivering a better customer experience.

Who Can Benefit From The Next-gen BI?

All the types of enterprises can benefit from the next-gen BI:

MNCs: As MNCs have to deal with massive amounts of data, they can benefit from next-gen BI for Big Data Analysis. Automation of monotonous business tasks and access to real-time insights that are very difficult to generate manually can be handy for MNCs or any business in general.

Mid-sized Businesses: As Mid-sized companies don’t have the budget for hiring a data analytics team, ‘Next-gen BI’ can help them with data visualization and exportation that can cut costs across the board. Therefore, it becomes more beneficial for businesses to utilize this software technology.

For Small and Medium-sized businesses utilizing BI-as-a-service is a great way to integrate this technology. By using BI-as-a-service, companies don’t have to invest in creating an on-premise infrastructure, making it a viable option. We will discuss more on BI-as-a-service in the further section.

Small-sized Businesses:

• BI’s desktop tools like Tableau and Microsoft Power BI are a more popular choice among small-sized businesses. Along with these desktop tools, many small-sized companies and startups go with the option of SaaS and cloud services.One of the reasons small-sized businesses opt for these tools is because of their simplicity. They work very similar to Excel and PowerPoint, applications in which most analysts already have high proficiency. Today’s BI tools also utilize AI-ML algorithms along with natural language for generating visual data.
• Microsoft Power BI is now integrated with Siri shortcuts. It means business owners will only have to say, ‘Hey Siri, open my reports,’ and the tool will present the user with all the relevant data. Power BI offers centralized reporting capabilities so that enterprises can make most of the self-service analytics.
• Tableau is another tool that is similar to Power BI.  It adds AI to the workflow and makes data more accessible by sharing the reports on Slack. Tableau has gifted its user with the ability to converse with the data. It offers suitable visuals and interactive explanations to all the data-related queries of business users. Tableau also provides AI-based predictions for Salesforce reports and sends them to Slack.
• Qlik Insight Bot is a conversational BI tool that provides automated insights and allows business owners to make data-driven decisions. The data and reports can be accessed via Qlik Sense and also through other platforms like Slack, Skype, Salesforce, and Microsoft Teams.  All the insights are driven by Natural Language Generation (NLG).
• Microsoft Power BI is now integrated with Siri shortcuts. It means business owners will only have to say, ‘Hey Siri, open my reports,’ and the tool will present the user with all the relevant data. Power BI offers centralized reporting capabilities so that enterprises can make most of the self-service analytics.
• Tableau is another tool that is similar to Power BI.  It adds AI to the workflow and makes data more accessible by sharing the reports on Slack. Tableau has gifted its user with the ability to converse with the data. It offers suitable visuals and interactive explanations to all the data-related queries of business users. Tableau also provides AI-based predictions for Salesforce reports and sends them to Slack.
• Qlik Insight Bot is a conversational BI tool that provides automated insights and allows business owners to make data-driven decisions. The data and reports can be accessed via Qlik Sense and also through other platforms like Slack, Skype, Salesforce, and Microsoft Teams.  All the insights are driven by Natural Language Generation (NLG).

Future of Business Intelligence

• According to Statista, the revenue of the BI software market is going to reach 32,652.95 million U.S dollars by 2026.
• In the future, the BI tools will get better at providing collaboration among the team. The current BI tools don’t have the feature to connect it with a broad network, but many researchers are working on it so that colleagues can work side-by-side, according to
• Third-party integration will also be introduced. It will simplify data processing and allow businesses to take appropriate action on the generated insights. The BI software and tools would become more accessible as they will send real-time insights to users via emails, text messages, and notifications.
• The ever-improving AI and ML technology will make it an even better self-learner. The coming generation of BI software is expected to become more intuitive and predictive in nature. Also, the AI/ML-based are good at learning from their past experience, making BI software more efficient with time.
• It will have Data Proactivity. This means that only relevant data will be provided to business owners, and all human efforts required to do this job would be omitted. This concept of Data Proactivity is co-related to third-party integration. Users don’t necessarily have to engage with the tools; instead, all the business data would be brought to users without any engagement.
• There will be an advancement in the network. A solid network is needed for any software. Many Computer Engineers are looking for a way to develop hardware networks and automatically increase the volume of data of BI tools.

Business Intelligence-As-A-Service

As discussed earlier, BI-as-a-service is another ingenious way to use BI technology if a company has limited IT resources at its disposal. Traditionally Business Intelligent solutions require extraction of the relevant data, organizing the data in the data warehouse, and then deriving insights from them by applying various algorithms.

But things have changed drastically ever since cloud computing came into the picture. It has made BI solutions more scalable and cost-effective for SMEs. Businesses can employ an end-to-end business intelligence-as-a-service solution instead of investing money in a data warehouse and maintaining it. Companies that already have incorporated BI solutions can also utilize BI-as-a-service for more streamlined and agile solutions which have better accessibility of data.

Sometimes people think BI-as-a-service is the same as Software-as-a-service. The SaaS providers only offer the part of what BI-as-a-service brings to the table. SaaS companies deliver an optimized user interface for interacting with data. But BI-as-a-service providers, along with intuitive UI, also do the job of extraction, organization and offer real-time insights into your data.

If you are also looking to hire a BI-as-a-service company, you must choose one that caters to all your business needs. As a BI-as-a-service company will do most of the heavy lifting, it becomes essential for you to choose the right Business Intelligence solution provider.

The question that comes to mind is how to choose the right Business intelligence solution.

Here are some criteria based on which you can make the right decision:

Reporting Abilities: The BI-as-a-service company should have the ability to provide dynamic reports that can be customized as per your insights requirements. By looking at these reports, you will be making important business decisions; therefore, the service provider must offer dynamic reports that perfectly fit your purpose.

Seamless Integration: The solutions that the service provider would deploy should be able to work in harmony with any other existing solution that you might have deployed in the past.

Accessibility of Data: You should be able to access data anytime, anywhere, and from any device you want. Look if the BI-as-a-service company has the ability to offer real-time insights and reports on any mobile application.  It will save a lot of time and increase the efficiency of the business.

Company’s Expertise: The employees of the service provider should have the relevant industry knowledge and experience. A BI-as-a-service company with a highly skilled team can let you gain a competitive advantage through their above-par BI services.

From the above article, we can see that the future of Business Intelligence and visualization is looking very bright. To ensure that the BI models are integrated seamlessly and working without any troubles, outsourcing this job to a BI-as-a-service company with a team of skilled and experienced professionals is another effective way to adopt this technology.

Sources: Statista, Gartner, Techcrunch, Dataversity, Deloitte, Businesswire, Blugranite, Forrester, ComputerWeekly

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However, Gartner predicts that by 2022, 50% of the brands may fail to unify their customer engagement channels, providing a fragmented customer experience that lacks cohesion, reliability, and context. To win business from customers undeniably influenced by the quality of brand interactions, it is now pivotal to invest in an omnichannel experience strategy that can make frictionless and personalized engagement possible for multiple touchpoints across their journey. It empowers enterprises to inspire customer delight by proactively offering more purchase and fulfillment options and successfully navigate channel disruptions to defend the integrity of their diverse revenue streams.

Extracting the optimum value of customer experience

So, considering its mission-criticality, how should a company that intends to go to market with an omnichannel experience delivery plan for its customers trigger the required transformation? Essentially, such a shift calls for a reimagination of how an organization approaches customer experience from a technological and cultural standpoint. It involves investment in top-line digital engineering skills and design thinking expertise that can meaningfully decode the brand-consumer dialogue across channels and attach the patterns of preferences to profitable business outcomes with confidence. True omnichannel experience is the sum of a host of incremental changes that include:

Re-engineering the CRM fundamentals making the landscape agile enough for deep API-backed integration with multiple channels. An intuitive and connected CRM is the heart of an impactful omnichannel CRM strategy that can deliver a 360-degrees view into customer behavior by assimilating sources such as social media activities, emails, incident tickets, and service desk cases into a single source of truth. This integrated approach is key to weaving personalized experiences that are holistic and resonate with actual customer needs.

Bringing insights from live customer interactions across channels to optimize the experience and providing a seamless omnichannel experience.  Today’s customer journeys aren’t straightforward and linear but an inter-connected series of handoffs between traditional and modern digital channels that can vary significantly. Providing a seamless handoff across all channels and ensuring that we have a customer 360 view is of paramount importance to ensure customer delight. This approach leverages cognitive technologies like Machine Learning, Natural language processing (NLP) and AI which helps create a personalized customer experience and plays a decisive role in improving customer satisfaction & brand recall and trimming the persisting marketing overheads.

Implementing customer analytics on top of the omnichannel CRM database, tailoring bespoke reports and customized dashboards that can permit various end-users within the value chain to be more customer-centric. Customer Experience Analytics, Retention Analytics, and Marketing Analytics offer end-to-end visibility into the brand-customer interactions across multiple channels, allowing marketing decision-makers to discover latent trends for realigning strategies.

Augmenting agent productivity with the proper training and tools that allow team members to embrace the culture of omnichannel commitment to the customer. It involves breaking down silos and sharing leads and customer information across the marketing ecosystem. Also, in an omnichannel environment where enterprise systems are integrated with third-party applications to enhance productivity, operating on multidimensional customer data needs adequate guidance to prevent the breach of customer data protection and privacy norms, mitigating security and reputational risks.

Business Impacts

A decisive move towards delivering seamless omnichannel experiences can unlock a new horizon of business opportunities, transform customer loyalty and convert them into promoters. Apart from this it helps improve operational efficiency, reveal new business streams, and elevate during and after-sales service quality. While ensuring round-the-clock availability, an omnichannel strategy can address the conventional inadequacies of face-to-face interactions like the short attention span of agents by distributing the workloads across various channels improving overall customer satisfaction.

Also, merging all digital marketing channels into a composite CRM with a customer 360 offers a complete view of the user persona, allowing marketing campaigns to be fine-tuned to relevance. Further, the availability of cross-channel customer datasets allows limitless analytics, equipping marketers to understand customer behavior patterns better and preempt foreseeable changes.

Conclusion

The omnichannel experience, while complex to orchestrate, is a critical differentiator in a closely contested market. Here, partnering with a digital engineering leader that can seamlessly converge the best of digital and in-person customer interactions to drive experience delivery is no short of strategic advantage. It can empower organizations to be nimble and pull ahead of the curve by delivering on overt customer requirements and subliminal expectations reflected through behavioral cues.

Sources: Salesforce, Gartner

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Customer experience (CX) analytics provides valuable insight into customer sentiments, sales, and expectations. By collecting relevant data and evaluating customers, brands can now easily make data-driven intelligent decisions improving their customer support and experience, and consecutively boosting their marketing campaigns, product innovations, and much more.

Growth Drivers Of Customer Analytics Market

Newer technologies have led to an increase in real-time data availability, and there are growing developments in analytics about customer behavior. According to Grand View Research, the global customer experience management market size was valued at USD 7,540.6 million in 2020. It is anticipated to increase by (CAGR) of 17.5% from 2021 to 2028.

As per the Forrester consumer survey of CX quality conducted in 2020, it was witnessed that 14% of brands improved their CX quality by finding and fixing problems primarily in their back-end systems and processes. In 2021, the number of brands improved CX and reached 27%.

The PwC Global Consumer Insights Pulse Survey 2021 states that the three top-ranked attributes in online shopping are Fast and Reliable Service which amounts to 42% and 36% for easily navigating the website, and 38% for in-stock availability of items.

These statistics show positive results on CX driving business growth and how by improving CX businesses can drive business sales and attract more and more customers.  But before diving into a comprehensive understanding of imbibing CX analytics into the workflow, let us first study the challenges in the CX segment.

RoadBlocks in Meeting Enriched Customer Experience

Though the evolution in technology is providing respite in business operations, organizations face major restraint in choosing a befitting technology to stream big data analytics.

Evaluating ROI of CX: CX leaders face hardships in getting budgets approved as customer experience Return on Investment (ROI) is not always calculated and measured, and without metrics like revenue, turn-around times, and value, ROI cannot be quantitatively predicted. The pain points in this arena are:

• Existence of discrepancies in data
• The unorganized structure where different departments have different needs
• Prevalence of traditional methods in data handling
• Lack of comprehensive schemes

In order to design a modern and responsive CX framework, CX metrics should be used in the current operations.

Identifying CX Problems: The growing customer base is causing everyday hindrances for CX professionals as they are drifted in all possible directions and finding it highly daunting to cater to vast customer expectations. Which is to be prioritized? Which areas need improvement? Which is the right strategy? Which is the right resource? Which is the best platform? Such concerns are piling upon CX leaders and consecutively are seizing the company’s opportunities to grab new businesses.

Lack of end-to-end Customer Experience: Often departmental and functional objectives plan and prioritize their goals with a single business focus in mind. There also stands a dearth of a seamless transition from one department to the other and a lack of transparency across business verticals. A proper mapping should be initiated keeping in mind the overall end-to-end customer experience.

Measuring CX Analytics

How are customers thinking? The current customer behavior trends have to be observed and the metrics should be considered before defining one’s organizational goals.

Identifying Customers and Touchpoints: Businesses can narrow their focus on customers by evaluating data such as who has purchased at a higher frequency, who have recently purchased, and the ones who are likely to purchase if offered customized deals. Such an overview of ideal customers helps enhance customer experiences. Companies can improvise on their customer service by catering to customer problem areas such as new customer onboarding, renewals, cancellations, website footprints, product returns, retracted customers, etc.

Customer Surveys: Customer Satisfaction Surveys help companies in strategically improving their products and services. Different types of customer experience survey aids in giving insights into the current market demands. For example, an enterprise can analyze its customers’ loyalty based on their recommendations made to their friends, colleagues, or acquaintances. This data helps to understand the current standing of the company and can help to predict the company’s future. Companies should periodically study customer feedback throughout their lifecycle.

Web Analytics: Web analytics helps companies in collecting, reporting, measuring customer website data and plenty of other contextual data. They can now map and improvise their entire website ecosystem by the medium of vital analytics such as page views, website traffic, click-to-action implementation, purchase behavior, drop-offs calculations, and other patterns.

Using Intelligent Data: Intelligent data provides knowledgeable insights into the latest market trends by analyzing details of the current CX status of the company and data related to roadblocks, campaigns, etc., which helps executives to better access the marketing activities and ROI across places, segments, services, products and many more. Using Intelligent Data helps to gain transparency in the work structure, plan future activities, effectively streamline operations thereby reducing advertising costs, strategically introducing a new stream of activities amid others.

Benefits of CX Analytics

Customer Experience is the backbone of any company’s growth and affects each and every aspect of marketing and business KPI.

CX analytics data helps in studying customer details pertaining to their demographics, behavioral patterns, and purchase history allowing the company to map their next product and service in line. Sales agents can use this data to enhance conversion rates wherein executives can make informed decisions to boost marketing, sales, and product development.

Central Database: CX Analytics defines itself as a centralized system that incorporates customer behavior analytics, and touchpoints across all platforms. It involves front-end interactions coupled with back-end data that are transferred from various tools that a particular enterprise is using to attract and engage customers. Here a customer journey’s footprints are cohesively collected into one central database system. The additional benefits include:

• The recorded time of a particular customer’s action on the channel
• Customer actions like data of a number of page views by a particular customer followed by their product purchase, transaction made, etc.
• A robust identifier to tie the activity to the user

Unique Identifiers: Companies embed in their systems newer tools to engage customers which help track unique identifiers. Data scientists spend long hours and efforts collating data from various tools and places which makes it highly time-consuming and tedious. However, CX Analytics uses a centralized ID graph system that analyzes customers’ journeys throughout and saves customers’ interactions in a data format as a whole.  It evaluates a customer footprint from the first moment, for example when he/she visits the website to become an identified customer, with details through click-to-actions like forms, email, phone numbers, internet accounts, cookies, etc.

User Case Study

A retail company leveraged data and marketing channels that weren’t being used and CX analytics provided added resources that helped drive the most out of digital transformation and customer experience management.  By creating a customized Customer Data Platform(CDP), the company was able to enhance its advertising and marketing internal culture. CX analytics helped this retailer with benefits such as:

• Unified customer views
• Complete and accurate, real-time customer data
• Personalization across platforms
• Smart segmentation
• Agile internal culture

Business interactions with customers can now be constantly analyzed with analytic tools helping them measure the products, services, and offerings of a company. CX teams can better evaluate current metrics, KPIs and challenges, and work towards prioritizing and tactfully investing in the growth strategies of the organization.

Sources: Grand View Research, Forrester, PwC.

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A Single Source of Truth

A great experience that can convert over 90% of the first-timers into brand loyalists is the sum of a broad spectrum of data points, including primary customer attributes, behavioral and attitudinal records, transaction history, and much more. CDP technology simplifies the task for the customer services teams by harnessing the required data from different sources, accelerating the journey towards exceptional service personalization. Investment in CDP assets can pull in a host of enabling capabilities for companies, allowing them to ingest customer data at the scale and speed of business, combine and orchestrate omnichannel feeds, and deliver real-time outcomes for stakeholders beyond marketing, in sales and UI and of course ensure compliance. Applying machine intelligence and Advanced Analytics on top of such a deep and comprehensive customer data processing ecosystem can bring forth the information advantage and functional ease, positioning organizations to be highly competitive in closely contested landscapes.

Enabling The CDP Outcomes

While CDP is an indispensable component of the modern marketer’s toolkit, organizations looking to transform can either opt for Commercial off-the-shelf (COTS) products or build their CDP stack. Although being substantially costly due to the hefty licensing overheads involved, the pre-packaged solutions can enable a rapid time to market due to their plug-and-play features. However, building a CDP from scratch can bypass the avoidable expenses and allow the flexibility to bring customized flavors that suit the marketing taste of a particular business, realizing value within merely 3-6 months. Notwithstanding the path a company is intending to walk, a CDP worth the investments in enriched CX should be able to deliver:

Simplicity: In the US, the estimated cost of customers switching due to poor service quality is $1.6 trillion annually. Also, Salesforce reports that 83% of the service agents acknowledge the desperate need for assistance to do their job well. When shifting customer expectations and business demands are already testing the limits of the service teams, next-gen data solutions must improve their access and maneuverability. For example, a CDP should neatly organize the available data for immediate use. Also, its setup and maintenance should discount the technical complexities otherwise involved in traditional data warehouses, and its outputs should be fit for consumption, even by a non-technical audience.

Single Customer View: 84% of businesses are more likely to purchase from vendors who understand their goals better. Also, 66% of the customers across B2B and B2C segments want their brands to be emphatic about their unique needs and expectations. This heightened state of awareness is only possible through a 360-degree view of the customer that a CDP should build on the data harnessed and assimilated into individual data profiles of each user. Further, it should read customer and related master data from semi-processed data sets, enrich data from multiple sources and merge various customer profiles and hierarchies to provide golden records. Finally, the validated CDP outputs should answer fundamental questions around how the end-users consume products and services and how successful they are in meeting their purchase objectives.

Customer Data Unification: Diversity is the cornerstone of a successful omnichannel CX delivery strategy, and today, more than half the businesses use at least eight channels to interact with their customers. A CDP should be capable of spearheading an effective information fusion strategy, pulling data from all channels, using event-based triggers into a single, interactive repository. The information pool should provide a reliable base for powering a broad spectrum of marketing use cases, from customer segmentation, acquisition, conversion to retention.

Data Sharing: The data contained within the CDP environment should be accessible to the other MarTech applications operating downstream. For instance, the demographics data correlated with the cost sensitivity insights of the prospective customers in CDP should guide the Campaign Management System on how to best appeal to the target audience.

Limitless Analytics: On top of all the digital engineering complexities under its hood, a CDP should be layered by enabling analytics. In fact, 90% of the global executives are dependent on data analytics to drive great CX, and 65% consider it vital to mission success. The visibility layer of CDP should enable enterprise decision-makers to discover a nonlinear correlation between divergent trends and patterns, allowing brands to connect meaningfully with customer requirements.

CDP In Action

But how can CDP bring the desired strategic and tactical depth for businesses looking to stay ahead of the curve by leveraging personalized CX? Perhaps this can be best understood in the context of the highly competitive Hospitality & Travel Industry manifesting solid signs of recovery as the COVID wave ebbs down. Here, customers interact with businesses across multiple touchpoints, including reservations and ticketing, check-ins, baggage information, airport information, passenger refunds, notifications, payment information, website traffic, and social media analysis, generating massive volumes of data in real-time or near real-time.

In the pre-travel phase, if a customer tweets or posts inquiring about beach destinations in an open social media forum, CDP can quickly align it with their previous bookings and purchase history and the trending beach destinations data to target the customer with preferred beach destination-related campaigns or offers, improving the conversion probabilities. Similarly, an airline can enrich the in-flight experience by tapping into the past ancillary bookings data and discovering attributes like the customer’s preferred cuisine, seating orientation, travel companions, and budget. Then, suitable offers can be pushed upfront to ensure that the traveler makes purchases that are most likely to make the trip enjoyable.

Also, CDP running on actual event-based scenarios can play a pivotal role in pre-empting negative experiences or compensating them early to prevent adverse brand impacts. For instance, in case of flight delays, customers can be offered relevant gift vouchers based on their social media activities as compensation, or their cab and hotel bookings can be auto-adjusted accordingly to deliver a one-order experience. Cost-conscious travelers considering themselves overcharged can be given a proactive price alert on their next booking, and apology emails can be issued to prevent a dip in the CSAT score.

Conclusion

The potential of CDP is not just limited to delivering a single customer view but helping organizations with the insights to put it into effect, elevating brand image. It helps companies target the right customer segments, user journeys, conversations, and response timing to improve customer lifetime value (CLV) and prevent churns. However, in an omnichannel environment, with an experienced digital engineering and analytics partner, businesses can effectively shape their CDP assets into a tool for revenue growth, even amidst wide-scale market disruptions.

Sources: Emplifi.io, v12data.com, sharpencx.com, Salesforce, Zoominfo, Forbes, hospitalitynet.org, Gartner.

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The year 2020 has been a point of inflexion, triggering an irreversible shift in how businesses and their customers interact and how value is perceived. Salesforce portrays the switch, reporting that 60% of interactions are currently taking place online, and 83% of customers expect flexible shipping and fulfillment options. Consequently, digital commerce, which was already in a solid stride before the COVID-19 landfall, has been thrown into top gear by the pandemic-induced changes, creating massive opportunities for growth and leaving businesses clamoring to keep pace. For instance, according to ‘DigitalCommerce360’, online retail sales surged 39% in Q1 2021. In response, enterprises must rapidly adapt by reinventing their organizations, culture, and technology landscapes to deliver agility and relevance.

Businesses are indeed alive to the demands of the New Normal and are not shy of joining the Digital Commerce bandwagon. Hampleton Partners observed accelerated M&A activities in the space, recording a phenomenal $117 billion in disclosed transactions. For example, a study using the EY Embryonic Platform found that May to July 2020 pulled in over $10 billion worth of investment into the retail vertical covering diverse initiatives including expanded logistics capabilities, asset-lite facilities, dark-stores established exclusively for online shopping, and digital leverages like AI and Blockchain.

Digital commerce and online buying behavior steering the shift in retail

In a closely contested space like retail, now twice as many insiders identify digital commerce as a long-term strategic priority compared to the pre-pandemic era. The trend is reflected by the fact that despite rising vaccination rates, collapsing daily average infections, and economies across the states consistently opening up, Americans are still bullish on online shopping channels, accounting for at least 20% of all retail purchases. Clearly, the businesses are in for a long haul, and HBR notes that retailers need to look beyond just investments and find out the enabling customer experience (CX) that can differentiate them against the competition.

With the decade’s worth of projected growth materializing within a quarter in 2020, the ground realities are, of course, lucid and remain primed for disruption. Here retailers looking to recalibrate their digital commerce roadmaps and elevate revenue stands to benefit from integrated solutions that can constantly contextualize and deliver customer-centric experiences with the evolving focus of the buying behaviors and market dynamics like:

Ease of payment: With more than 77% of the Gen Z-ers looking for new ways to consume existing products and services, purchase decisions are made by much more than just affordability. Price is no longer the only deciding factor in how an online retail customer perceives a brand. The ease of payment, integration with the customer’s preferred banking channels and wallets are also emerging as significant determinants for customer stickiness. In fact, ‘CustomerThink.com’ found that nearly 50% of consumers who can’t use their preferred payment method are likely to abandon a purchase. Further, 70% of the online shoppers confessed that the checkout experience is their most persisting pain point.

Here investments in integrating with multiple payment gateways at a lower per dollar spent commission can improve the checkout experience for the customers, keeping them engaged and loyal. Also, Gartner reveals that seamless digital payment methods, discount vouchers, and hassle-free refunds to the actual source of payment can instill higher confidence in online shopping for at least 36% of the customers.

Last-mile fulfillment: The New Normal has indeed raised the bar higher on the door-step delivery of products and services, and consumers today are equally focused on accessibility and convenience as they are on affordability, if not more. Fitness equipment, streaming devices, white goods, etc., were traditionally purchased offline after a thorough comparison of their price and features. But at present, there has been a pronounced spike in the purchase of these products through digital commerce and online delivery channels.

A study found that 79% of the US consumers are not ready to compromise on the delivery of their purchases due to COVID-related disruptions, indicating that it is no longer a reasonable excuse for service outages and unavailability. To stay competitive, retailers can no longer consider fulfillment in isolation and must imagine it as the cornerstone of high-quality customer experience. It calls for integrated logistics support and WMS availability across geographies that can be leveraged on-demand to ensure end-to-end coverage of the fulfillment workloads with high reliability.

Omnichannel engagement: In the pre-pandemic years, consumers preferred to speak with a customer support agent for clarifications. But in the New Normal, since there are fewer support agents accessible due to the inherent change in the nature of work, most of the queries are being serviced by websites/mobile apps and chatbots. However, this has also made the customer extremely aspirational. Now they expect to engage with the brands of their choice via mobile or web, online marketplaces, or even via social platforms.

Today, 83% of customers want to interact immediately with a service agent while connecting with a brand, up from 78% in 2019. Also, 68% of the customers expect businesses to demonstrate empathy. In fact, now, customers turn to an average of nine channels to browse product listings, get educated and make purchases. Therefore, the retailers must resolutely invest in an omnichannel CX strategy. Digital solutions that can successfully establish a single source of truth for engagement across all channels and make the personalized and contextual delivery of experience possible can improve customer satisfaction and improve churn rate.

The contemporary omnichannel world promises exponential growth in businesses’ opportunities to engage, sell, and improve revenue realizations. Nevertheless, retailers must understand that each digital commerce channel will present its unique challenges in improving customer experience. Website designs may allow only so much content to drive informative conservations among consumers for high-consideration purchases. Mobile commerce might limit the branding elements necessary to build ongoing affinity. A lack of tech maturity might undermine efforts to deliver a good experience via social marketing.

The challenges can be further aggravated by the choices and preferences of the customers who are likely to engage with businesses in multiple formats and across multiple touchpoints, making the pursuit of an excellent customer experience one that needs to weave together information from disparate sources. Here a business can pull ahead of the competition with the right digital engineering acumen and impactful experience delivery capabilities that strikes a chord with the customers, evoking positive brand sentiments, compelling them to revisit, and of course, repurchase!

Conclusion

The happenings of the last 18 months have driven one of the sharpest growth in the digital commerce vertical. They have projected broad-based and observable shifts, from payment methods, supply chains, and distribution networks to consumption behaviors. For example, several manufacturers turned to Direct-to-Consumer platforms with uncertainty in the supply and distribution operations. Likewise, as more and more brick-and-mortar stores went online, even consumers adapted by opting for curbside pick-up trends across different categories. But regardless of how consumer behavior and preferences continue to evolve, to stay competitive, the retailers must attempt to use the current tailwind brought by the new digital commerce dynamics to foster enduring customer relationships that can stand the test of a disruptive future.

Sources: Salesforce, DigitalCommerce360, Hampleton Partners, Harvard Business Review, CustomerThink, Shopify, Gartner.

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