Digital Transformation Archives - BotCore

Low Code vs Pro Code: The right platform usage for digital transformation

Abhishek Shanbhag — Tue, 15 Jun 2021 09:08:00 +0000

Low Code vs Pro Code: The right platform usage for digital transformation

The COVID-19 pandemic has accelerated the pace of digital transformation and the adoption of technologies, such as analytics, AI, mobile connectivity, cloud, etc. To adjust to the new ways of working and transform existing workflows, the business world now needs hundreds of simple and complex apps.

However, when it comes to coding such apps, there is no one-size-fits-all solution. Low code app development (LCAPs) platforms are the new rage. With a visual development interface and drag-and-drop simplicity, they allow pro and citizen developers alike to build more apps in a shorter period, at lower costs, with little or no coding requirements.

The global low-code development platform market is valued at $12.85 billion in 2020 and is expected to reach $65.15 billion by 2027 with a CAGR of 26.1% over the forecast period.

While the speed and practicality of low-code platforms have infused agility in business operations, they can’t account for the entire range of complex enterprise apps at the modern workplace.

Instead, app developers look for platforms that drive productivity without compromising on features they need to deliver a seamless mobile or web experience.

That’s where a low-code app development platform with pro-code support comes into the picture.

Let’s explore in detail.

Low Code Platforms: Pros and Cons

As seen above, a low-code app development platform (LCAP) empowers business users to develop and deploy apps quickly and seamlessly.

Users can create business applications using point-and-click configuration instead of dealing with the source code. An LCAP includes pre-built components, graphical development tools, reusable building blocks, and business logic and workflows. Hence, users with varying levels of technical prowess can build apps using a “drag-and-drop” approach.

Low-code platforms, such as Microsoft PowerApps and Google App Maker, free up the IT teams from the constant demands for new enterprise applications. IT personnel can then focus on strategic business needs and keep the momentum going on digital transformation initiatives.

Research has estimated that low-code platforms may reduce development time by up to 90% in some cases.

However, is low-code enough?

The primary issue with low-code platforms is that sooner or later, you’ll need to do something that isn’t a part of the pre-built components. After all, the drag-and-drop functionality cannot cover every scenario.

Enterprise applications, particularly ERP and legacy apps or systems, are highly complex and manage multiple data sets. Even though LCAPs provide service integrations with ERPs, certain data sets may be outdated, or the business logic that can be captured in these apps may be limited.

Often, with a low-code platform, you may not be able to connect these systems and customize them as per your needs.

So, what is the solution?

Low-code + Pro-code

Restricting low-code functionality to front-end design or simple apps does not benefit cross-functional teams and isn’t sustainable in the long run. So, what is the right platform usage for your digital transformation needs?

Connecting low-code and pro-code platforms provides a dynamic framework of front and back-end tools that allows developers to design apps with speed and minimum time-to-market without sacrificing customization and sustainability.

Pro-code is the classic complete code programming used by software engineers and developers to build complex software.

Low-code + pro-code platforms offer rock-solid security, integrated DevOps and automated testing, and the ability to leverage advanced technologies, including AI, augmented reality, and much more easily.

Ultimately, the ability to connect the two unlocks the best of both worlds, i.e. –

A professional-grade infrastructure that can handle complex integrations and coding
Improved efficiency, higher developer productivity, and reduced costs with the low-code functionality

How can Acuvate help?

As a Microsoft Gold Partner, Acuvate helps clients build enterprise apps using Microsoft PowerApps. A low-code platform, PowerApps allows enterprises to develop low-code apps for various use cases using in-built templates, canvas, and model-driven scenarios.

They can generate extensive applications, which are customized to solve individual business needs and can run on any device.

Additionally, they may access many advanced functionalities previously available for professional developers only.

For such professionals, PowerApps offers several key advantages –

More than 200 connectors to proprietary data sources
Code plug-ins for advanced business logic
Data gateway to securely integrate with services running on-premise
Data integrator and Power Query tools for bringing data into CDS
Less coding plus automated testing.

Moreover, organizations can bring PowerApps and Microsoft Azure together to build rich functionality in a low-code platform and turn business needs into custom apps.

Learn More: Why PowerApps and Microsoft Azure are better together

To know more about our PowerApps services, please feel free to schedule a personalized consultation with our experts.

The post Low Code vs Pro Code: The right platform usage for digital transformation appeared first on BotCore.

How Conversational AI is transforming Digital Marketing

Abhishek Shanbhag — Wed, 14 Apr 2021 06:58:00 +0000

How Conversational AI is transforming Digital Marketing

With customer experience (CX) becoming a critical deciding factor in the choice of brand, organizations are looking at ways to engage with customers across all digital marketing platforms.

As customers increasingly demand round-the-clock access to information, social media and instant messaging apps replace phones and email. Companies, particularly FMCG brands, have started responding by implementing conversational AI experiences.

Mark Zuckerberg once said, We think that you should just be able to message a business in the same way that you message a friend. You should get a quick response. And it shouldn’t take your full attention like a phone call would. And you shouldn’t have to install a new app.

Conversational AI chatbots leverage machine learning (ML) and natural language processing (NLP) to mimic real people and hold human-like conversations with customers. Chatbots embed easily in day-to-day messaging apps. They are reliable and accurate and enable companies to interact with their customers all-day. Moreover, they are intelligent. Capabilities like dialog management and sentiment analysis help chatbots gauge context and customer emotions and respond to their needs better.

Conversational AI bots help customers seek information, purchase products and services, and enable brands to push the latest offers and marketing campaigns.

Let’s understand further how conversational AI is transforming digital marketing.

Revolutionizing digital marketing with Conversational AI

1. Access information and perform simple tasks

As seen above, conversational AI chatbots are available 24X7, provide instant answers, and can be deployed on multiple channels.

They can answer simple customer queries, such as, “What is the status of my flight” or “When will my order reach me” or “Is this car available in red.” Moreover, they can handle multiple requests simultaneously, easing the burden off support staff and helping organizations provide quick, interactive support at scale. Additionally, chatbots can be used to execute customer requests, like booking a hotel room, transferring money from one account to the other, etc.

2. Educate customers on how to use the product

Recently, organizations have started using chatbots to recommend how customers can use the product or service.

Take this example – Quaker Oats, a famous food brand, uses its Facebook Messenger brand called Otis to recommend oats recipes, set reminders for overnight oats, and assist customers with online shopping. Users may use a combination of text and emojis to discover new ingredients and recipes.

3. Update customers about new products and offers

Brands can leverage AI-enabled chatbots to study customer profiles and proactively inform them about the new products, latest offers on products they may be interested in, upcoming sales, tailored product recommendations, etc.

Such services add a new dimension to their marketing endeavors and go a long way in building brand loyalty.

4. Capture customer feedback

To improve product design and quality, make meaningful adjustments in the product development process, and adapt to evolving customer needs, organizations can use conversational AI chatbots to capture customer suggestions and feedback.

Feedback may be in the form of a 1-10 rating scale, or the chatbot may request the customer to provide a written review, or else the customer may upload product images and videos.

The current scenario

Organizations deploy chatbots on various messaging apps and platforms, the most popular being Facebook Messenger, WhatsApp, Telegram, and official company websites.

With over 300,000 active bots on Messenger and approximately 1 million new WhatsApp users every day, Deloitte predicts that by 2022, “we’ll be talking to bots more often than we talk to our own spouses.”

5 Examples of companies using conversational AI in their marketing mix

1. POND’s

We, at Acuvate, built POND’s Facebook Messenger bot called SAL that was launched across nine countries. SAL leverages augmented reality to provide skincare recommendations across four areas – pimples, wrinkles, spots, and uneven skin tone. Customers need to upload a selfie, post which SAL gives a personalized skin diagnosis and recommends products accordingly. SAL managed a 98% positive customer review, with the brand generating 15 times higher purchase intent.

2. Adidas

Adidas added an exciting element to its marketing mix with its “Rent-a-Pred” chatbot on WhatsApp to assist recreational football teams hire a professional athlete if a player backs out at the nth hour.

The campaign, which included the likes of football star Kaka, generated significant buzz around the brand and helped Adidas market its Predator20 Mutator footwear.

3. Whole Foods

Whole Foods’ chatbot for Facebook Messenger lets customers find recipes based on their favorite ingredients, dish type, dietary preferences, etc. Again, just like Quaker Oats, customers may use both text and emojis to find the recipe of their choice.

Also, the chatbot helps customers check if their nearest Whole Foods store has the necessary ingredients for a particular recipe.

4. Absolut Vodka

When Absolut Vodka launched its limited-edition collection in Argentina called Absolut Unique, it organized an exclusive party to generate excitement and positive word-of-mouth.

Since only two members from the general public could attend the party, people had to convince Absolut’s virtual bouncer, Sven, to give them the tickets. The campaign was a resounding success, with the company receiving more than 1000 hilarious videos, images, and voice notes from users on why they should be invited to the launch.

5. Dominos

Dominos Pizza launched its Facebook Messenger chatbot named Dom to help customers view the menu, place an order, track existing orders, and chat with customer support.

How can Acuvate help?

At Acuvate, we help clients build AI-enabled chatbots with our enterprise bot-building platform called BotCore.

Our chatbots can be deployed with minimalistic coding requirements within a few weeks and across different channels, with channel-specific API. BotCore’s bots support multiple languages to help you reach out to a global consumer base.

To know more, please feel free to schedule a personalized consultation with our BotCore experts.

The post How Conversational AI is transforming Digital Marketing appeared first on BotCore.

6 Top CIO Priorities For 2021

Jagan Jami — Fri, 08 Jan 2021 09:03:00 +0000

6 Top CIO Priorities For 2021

In 2020, CIOs and other IT leaders have solved several unprecedented challenges and became key enablers in business continuity. CIOs are now in a dilemma regarding the orientation of their efforts and resources in 2021. While building resilience is still a priority, it’s time to plan for recovery post pandemic.

As millions of workers shifted to the remote setup, and customers moved online, businesses leveraged digital technologies to augment customer and employee experiences.

In a Harvey Nash/KPMG 2020 CIO survey, which polled 4,200 IT leaders, 61% of CIOs say they feel more influential than ever before, courtesy of their work to help hedge their businesses against the coronavirus.

However, rapid digital acceleration and adoption of cloud and other technologies have also brought many pressing issues to the forefront – the most significant one being the management of an increasingly complex IT infrastructure.

In a survey conducted among 1000 IT leaders, 63% reported technology management had become more difficult.

Yet, leaders globally have accepted the importance of technology as a business growth accelerator and will continue to work upon that in 2021 – even with tightened budget restrictions.

Let’s explore the top CIO priorities in 2021.

Top CIO Priorities For 2021

1. Low-code development

The onset of the coronavirus pandemic put immense pressure on the IT department to quickly develop new business apps to meet changing organizational needs. Faced with a massive resource crunch, many IT leaders implemented Low-code Application Platforms (LCAP) to enable business functions to develop and deploy custom apps quickly, and by themselves – with little to no reliance on IT. These platforms don’t require users to have prior coding experience.

Low-code platforms empower pro and citizen developers alike to build apps seamlessly, using canvas and model-based scenarios and automated testing. With LCAPs, CIOs can save costs in the long run, as –

Less coding means more apps can be developed in a shorter period of time
With low-code requirements, basic and quick apps, can be developed by less experienced employees, while professional developers can create complex solutions – but in much less time and cost.

As companies continue to focus on agility in operations and make their way to recovery in 2021, implementing low-code platforms like Microsoft PowerApps will be a top CIO priority in 2021.

Learn More: How Low-Code Application Platforms Are Driving Agility In the New Normal

2. Getting To The Next Phase of Chatbot Maturity

AI-enabled chatbots and virtual assistants gained widespread popularity in 2020.

To reduce wait-time and provide support at scale at lower costs, leaders implemented AI bots that leveraged natural language processing to hold human-like conversations with customers and employees and resolve queries quickly.

We have seen companies implement multiple employee-facing chatbots for a variety of use cases – There is a chatbot for HR support, another chatbot for IT issues, one more bot to let employees access information from LoB systems.

In 2021, we will see CIOs unifying all these individualized bots into a single aggregator bot or an intelligent employee assistant to provide a consistent user experience and reduce maintenance costs.

Similarly many customer-facing chatbots that were deployed during the pandemic focused solely on delivering support and quick information. In 2021, as recovery and bottomline becomes critical, leaders will focus on building brand loyalty, driving retention and generating revenue through chatbots. Chatbot use cases will be expanded to upselling, cross-selling, providing personalized recommendations and user experiences.

As such, capabilities like conversational analytics, sentiment analysis, and omnichannel engagement will become critical.

3. Enabling The Return to workplace

Another critical area that CIOs will prioritize is preparing their organization for a hybrid workplace setup in 2021. This will include investing in the right technology needed for a safe and smooth transition back to the workplace while also ensuring the availability of better collaboration tools, resources, and training essential to function remotely for an effective hybrid model.

Leaders must strike a delicate balance between resuming standard operations and managing the realities of the post-COVID era, including redesigning workplaces and redefining workflows to keep employees safe, productive, and aligned.

Autonomous digital workplace platforms and low-code return-to-workplace apps are a few solutions CIOs can consider.

Learn More: Getting Ready for the Hybrid Workplace: The New Normal of Work

4. AIOps

Owing to the pandemic, organizations around the world adopted digital transformations at an accelerated pace to be able to function in a remote setup and build agility and resilience in their operations.

However, as the number of apps, servers, and systems grew, it gave rise to an increasingly complex IT infrastructure, which can no longer be managed and protected by traditional performance monitoring systems and human agents. Even a single IT outage could cripple business operations and cost millions of rupees in revenue. As seen above, more than 60% of IT leaders felt technology management had become more difficult.

That’s where AIOps came into the picture. Artificial Intelligence for IT operations, also known as AIOps, leverages machine learning, big data, and analytics, analyzing heaps of IT data generated, diagnosing issues in real-time, improving application performance and uptime by predicting future outages, and reducing operations and maintenance expenditure.

Therefore, as businesses continue to operate in a highly dynamic and componentized IT landscape, the adoption and implementation of AIOps for IT operations management and cybersecurity will be a major CIO priority in 2021.

5. Reducing silos and streamlining the technology landscape

COVID-19 has accelerated digital transformation journeys and increased adoption of various AI and remote working technologies. While these initiatives did ensure business survival in 2020, they are now posing a new challenge – increased technological silos. In 2020, companies rushed into digital transformation – but with no solid strategy. We have seen the implementation of various siloed remote working apps, custom mobile apps, and several function-specific systems that have individualized use cases and served for one-off purposes.

Now is the time for CIOs to unify all these apps together with a Digital Experience Platform (DEX) and reduce silos. A DXP acts as a centralized digital platform which offers flexible app integrations and easy extensions for emerging business needs.

6. IT as an enabler of business growth

The drastic shift in consumer and employee habits has completely transformed the expectations from IT. For CIOs, the opportunities expand beyond routine – building digital capabilities and getting new tools and systems for the organization.

Instead, the expectation is to enhance core capabilities and align outcomes to key business goals. For example, say you are working to increase revenue by 10% through digital commerce. Everything you do, including your people, technologies, and processes, must then tie back to this goal in an outcome-driven environment.

Thus, reinforcing the role IT plays as a strategic enabler of business growth will be a top CIO priority in 2021.

Final Thoughts

As digital transformations have led the way for change in 2020, the role of CIOs has come to the forefront. They have not only ensured that businesses transition smoothly to a remote setup, but have also integrated operational continuity as a critical element in their overall IT strategy.

CIOs have been given buy-in from every level of the organization. In 2021, as the role of IT into a driver of business growth, there is an enormous opportunity for CIOs to transform and future-proof their businesses for a new normal.

If you’d like to learn more about this topic, please feel free to get in touch with one of our customer service transformation experts for a personalized consultation.

The post 6 Top CIO Priorities For 2021 appeared first on BotCore.

Top 5 Myths About AI You should stop believing

Abhishek Shanbhag — Mon, 11 Feb 2019 19:46:00 +0000

Top 5 Myths About AI You Should Stop Believing

As much as AI and its abilities are being spoken about and speculated today, there are quite a few myths that are doing the rounds as well. While some believe that it to be a deus ex machina, a tool that can resolve seemingly unsolvable problems, there are others who see it as just hype that will eventually die down. The reality about AI however, lies somewhere in between.

With the growing need for technology to make processes more efficient and provide companies with a competitive advantage, it is crucial to understand how AI can create value in your business and what its limitations are.

Alexander Linden, a Vice President Analyst at Gartner says “Business leaders are often confused about what AI can do for their enterprise. This is understandable, as there are many definitions and variants of AI that are present in the general discourse”. Misconceptions and a lack of understanding about AI is an impediment for IT leaders who are trying to incorporate AI in their organizations.

In this article, we bust the 5 myths that are often associated with AI and make a case for why you should stop believing them NOW.

The top 5 AI MYTHS

1. There Is No Need For AI Strategy

As the abilities of AI are evolving, organizations should consider tapping into its capabilities and understand the potential impact this technology may have in addressing the organization’s business needs.

Deliberately refraining from using AI is akin to forgoing the next phase of automation and could put your organization at a competitive disadvantage.

Even if you choose to abstain from adopting an AI strategy for your company, this decision should be made on pragmatic grounds supported by research and robust data. The need for AI in your organization should also be regularly evaluated and modified to fit the organization’s evolving needs.

2. AI Is All About Automation

While it is true that AI can automate several manual tasks, its range of capabilities are not always synonymous with automation itself. Automation is a subset of AI.

According to an extensive survey by Deloitte Research of AI applications in various industries, AI applications fall into three categories: product, process, and insight.

Product applications use AI to provide a better experience for the end user, either by enabling “intelligent” behavior or by automating tasks that a human user often performs.
AI is used in Process applications to enhance, scale up, or automate business processes.
Insight applications on the other hand use AI, machine learning and computer vision to analyze data and glean insights in order to drive better business decisions.

In only some of the cases is AI really used to automate human work. More often, AI is used to perform tasks that are unattainable by human cognitive abilities. While automation refers to the completion of a task without human interference, AI is used to power machines, making them capable of thinking or at least making intelligent decisions based on a series of predefined models and algorithms.

3. AI, Machine Learning And Deep Learning Are The Same

AI, Machine Learning and Deep learning are often interchangeably used or misunderstood to be the same, despite being fundamentally different.

Artificial Intelligence is the human-like intelligence exhibited by machines that encompasses various human cognitive abilities.
Machine Learning is a set of algorithms that allows a program to generate results accurately without the results being fed into the program explicitly. ML is in fact one of the tasks that AI performs by continually learning from the data fed into it and can be referred to as a sub-discipline of Artificial Intelligence.
Deep Learning, however, refers to the algorithms used to solve problems based on neural networks designed to mimic the neurons in the human brain. DL is one of the specialisations of ML and in turn, one of the aspects of AI.

4. AI Will Replace Humans

A common AI myth is that it can outsmart and replace humans at some point. This misconception is also one of the major barriers to AI adoption.

While it is true that AI makes machines extremely intelligent, we need to understand that machines cannot acquire such a potential all by themselves. The capabilities of a machine is limited to the data that is fed to it by a human being and the actions that they have programmed the machine to carry out.

It is important to identify the obvious benefits AI and ML add when it comes to automatically identifying patterns from an expansive amount of data with little to no human intervention. However, the algorithms and models that make this feat possible, have to be built by humans. So essentially, AI only can get as smart as a human mind can make it.

Another crucial feature that sets human intelligence well above AI is that humans are capable of recognizing when there is a problem or redundancy with a certain approach they are taking. AI models on the other hand, tend to pursue the best possible answer out of nearly infinite possibilities, even if it leads to them never exiting the process.

5. AI Is A Cost-intensive Undertaking

AI is looked at with apprehensive often, based on the assumption that it is going to be a costly investment for the company. However, high cost is not the case for AI in general. There are many AI tools that are available for businesses that do not demand an exorbitant investment to implement AI solutions. Some important AI solutions which are cost effective and also yield a huge ROI and several business benefits include chatbots, RPA, modern intranets with AI capabilities and advanced analytics.

On the other hand however, AI development does require expertise in programming languages and development practices. While hiring data scientists for this job may rack up costs, organisations can consider training the existing resources to effectively implement the algorithms themselves.

conclusion

It is necessary that companies take concerted initiatives to develop comprehensive strategies that accommodate AI and prepare themselves for futuristic environments that are compatible with AI powered technologies. It is imperative for companies to act on these initiatives before any new market disruptors jeopardise the competitive edge the organization may hold in the industry.

This demands the leadership of organisations to have a pragmatic and precise understanding about AI’s capabilities and its trajectory into the future. Having a strong academic foundation and practical experience in AI among the leadership allows organisations to avoid misinterpretations and misleading myths about AI.

Adopting AI just for just a few functional areas will be ineffective in making a great impact on the organization as a whole. Hence, companies must try to incorporate an effective blend of embedded, edge and centralized intelligence systems across all functions and teams.

Adopting AI and related technologies in building an intelligent business environment will strengthen the alliance of humans and intelligent machines and produce a powerful workforce for the future. Companies must acknowledge that humans and machines will continue to be the indispensable building blocks of the new workforce and plan to utilise their combined strengths effectively.

Acuvate believes that organizations need AI to accelerate their digital transformation journey. Our range of solutions and services around conversational AI, digital workplace, business intelligence and RPA are built with a strong AI foundation. If you’d like to learn more about AI and its capabilities, please feel free to get in touch with one of our AI experts for a personalized consultation.

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