Chatbots are core to our digital lives in 2023 whether or not we’re properly aware of it. From website help popups to customer service chatbots, it’s safe to say this technology has reached a point of ubiquity for anyone who spends any time online. On both the customer side and the business side, chatbots present all of us with an opportunity to work smarter, streamline our tasks and activities, and manage our time more thoughtfully.
In data from Statista released in early 2023, the financial figures for this market shows that it is, understandably, experiencing ongoing growth as many Artificial Intelligence (AI) technologies are. Current data forecasts that the chatbot market will reach a value of around $1.25 billion USD in 2025. Major expansion in this space has been attributed to the global market events of the Covid-19 pandemic through to developments in AI in 2022. All-in-all, the range of chatbots that are being used vary considerably and this is constantly evolving: some chatbots have specific sets of rules that guide development while some chatbots are being optimized with ever-diversifying sophistication.
More detailed market data suggests that this is a space that is flourishing across verticals; most recently, the large enterprise segment led the global chatbot market with a revenue share of 51.7 percent however there is steady expansion across small, medium, and large business classifications. “Since the chatbot automates a portion of the customer service and sales processes, the enterprise can reduce its operating expenses, which results in significant cost savings,” says a report from Straits Research that then explains further, “This is one of the primary factors driving growth in the chatbot market.”
In this blog, we will cover six areas about the current state of chatbots and how to use them:
- The current state of the chatbot AI market — a starting overview for 2023
- The technology behind AI in mobile app development
- A refresher on the six different types of chatbots in mobile app development
- Why chatbots continue to be central to customer service for software, websites, and mobile app development
- Why conversational AI is so cutting edge in mobile app development right now
- Seven ways to update how your business is using chatbots and conversational AI in its mobile app development in 2023
The current state of the chatbot AI market — a starting overview for 2023
The widespread use of this AI technology across customer service segments in a number of industries is therefore just as important as in their first major market wave in 2016 — or as Eli Israelov writes for Forbes, “The coming year will be key for this digital transformation.”
The number one contributing factor for this can be summed up as the ChatGPT effect.
In short, the state of the chatbot market can be linked to OpenAI’s announcement of the ChatGPT prototype in late November 2022. In just three short months, this prototype has:
- Resulted in numerous copycat versions in the App Store and Google Play
- Had Microsoft making further multibillion dollar investments in OpenAI
- Accrued 100 million users within two months of launch and broken the previous record for global user growth
- Led to a pilot of ChatGPT Plus for professional subscribers
Further to these developments, Microsoft has now launched its Bing AI chatbot ‘Sydney’ (powered by ChatGPT) and Google has launched its own AI chatbot, Bard, powered by its proprietary LaMDA technology. Many experts believe the Bing AI ‘Sydney’ and LaMDA AI ‘Bard’ are in response to OpenAI’s ChatGPT, with all three using experimental chatbot technology.
Almost a third of the way into 2023, this ‘AI Race’ playing out with chatbots is only getting started. The large language models powering these generative and conversational AIs are able to engage with users on philosophical topics, devise original poetry and essays, correct code, and summarise articles. Many people — both professionals and casual users — have been wowed by these chatbots though they’re not infallible; thus far, ‘Sydney’ has been accused of “acting unhinged”, ‘Bard’ gave incorrect information about Google-funded products, and, ChatGPT has encountered issues with accuracy. This is not to say this chatbot technology is a failure, rather it is to flag initial shortcomings.
Conversely, these developments in chatbots are driving discourse around what the technology that powers the conversational AI is going to be like moving forward. Early pundits make the case that this “chatbot-enhanced search” is newly indicative of what the future of search engines, customer service interactions, and assistant technology might be like. Dan Milmo writes for The Guardian, “However, the phenomenal interest in ChatGPT, which signed up more than 100 million users in two months, shows considerable public appetite for an AI-enhanced search experience.”
The technology behind AI in mobile app development
So, what does this mean for the technology currently powering the AI in mobile app development? The technology that drives the most common AI in mobile app development can be defined as tying in to the following aspects of development:
- Real-time translation
- Deep learning and machine learning
- Managing workflows and user experience (UX)
- Search engine optimization
- Logical reasoning
- AI and IoT amalgamation
- Security with biometrics
- AI-powered chatbots
All of these aspects have value to mobile app developers, business owners, and users alike. Though we are focused on the last aspect (AI-powered chatbots) for this article, all ten of these are essential in 2023. For efficiency, accuracy, and quality, AI offers myriad benefits to everyone. Integrating these functionalities results in just some of these desirable outcomes:
- More affordable apps
- Smarter apps that collect user data to meet customer needs and inform updates
- Identifying technical issues that affect UX
- Improve security, identify threats, and overcome macro and micro cyberattacks
- Regular, reliable customer service and escalation automation
- Scheduled functions that ensure the user receives payments and messages
AI in mobile app development is as much of a default as the AI that powers search engines or allows us to access Internet of Things smart devices. As this technology continues to evolve and transform our world, apps will naturally become even more powerful and we’ll continue to experience this across paradigms.
A refresher on the six types of chatbots in mobile app development
Understanding the different kinds of chatbots is worthwhile before we delve deeper into how businesses can update and elevate their current chatbot strategy. The following chatbots are used in mobile app development:
- Keyword Recognition-Based chatbots — Use Natural Language Processing (NLP) to respond to user inputs; not flawless as they can fail with too specific, too similar, or too nuanced inputs.
- Menu/Button-Based chatbots — Coded with a ‘design tree hierarchy’ that creates an ‘if this then that’ navigation. Generally used for FAQs in a flow chart structure to determine next steps for a user.
- Machine Learning chatbots — Use Machine Learning (ML) and AI that builds the chatbot with data and algorithms to imitate human learning and thinking; in use, the chatbot can interact with the user and leverage data inputs to intelligently and responsively engage.
- Linguistic-Based (Rule-Based) chatbots — Use predictive language based on conditional user inputs to deliver a response; a rigid design that requires specific inputs for accuracy therefore there can be issues.
- Hybrid Model chatbots — Combines both rule-based and AI capabilities to manage data volume; without the hybrid capabilities, these chatbots can’t handle high data volumes.
- Voice Bot chatbots — Designs seen that use this proprietary AI in hardware, e.g. Amazon’s ‘Alexa’ and Apple’s ‘Siri’, that interact with user input.
In mobile app development, these different chatbots can all be used — in varying forms — to identify problems and deliver customer service. Additional functions that developers can utilize are data gathering, analysis, and review of patterns that can then be transferred into user prompts to drive engagement. Chatbots with AI, such as those that use different forms of ML and NLP, are now considered the future of the technology. This enables conversational AI for realistic, natural responses and greater reliability in an app’s customer service, userflow, and business operations. The outcomes are, quite desirably, increased customer satisfaction, higher profits, and a stronger brand profile as IBM outlines, “Conversational AI is a cost-efficient solution for many business processes.”
Why chatbots continue to be central to customer service for software, websites, and mobile app development
Customer service and chatbots now tend to go hand-in-hand. “When people think of conversational artificial intelligence, online chatbots and voice assistants frequently come to mind for their customer support services and omni-channel deployment,” IBM attests.
The pillar reasons that chatbots are central to customer service — especially in mobile apps — are:
- Accessibility — Time and inclusivity both improve access as chatbots are available round-the-clock and users can adopt them entirely to their own needs.
- Consistency — For both users and businesses, the customer service standard is consistently the same which can limit misinformation, maintain messaging, and inaccuracies are more explicitly spotted compared to user error.
- Affordability — Enables businesses to plan their expenses according to demand and without compromising customer service standards.
- Task Management — Chatbots can lower wait times, manage multiple requests, and swiftly support basic requests freeing expert personnel for high-level support.
- Resource Management — Diversifies customer service offering in both type and allocation of funding to make business offerings more dynamic.
- Engagement — Chatbots are always there to help users and can be prompted by pattern recognition.
- Data Utility — Better serves customers based on measurable, activity-based needs in conjunction with their inputs.
- Personalization — Delivered thanks to Data Utility to perfectly respond to individual requests and tailor-make their UX.
According to Grand View Research, deploying Chatbots can automate approximately 35 percent of the task done by an individual and their expanded findings show that this can result in annual savings in macro costs at a huge, substantial scale. This is not purely tied to automation that eliminates employees though this is a belief still held by some people. Customer service can actually be transformed through the use of chatbot technology and it’s down to businesses to make their customer care offering so strong that everyone experiences the returns.
Why conversational AI is so cutting edge in mobile app development right now
We’ve discussed the developments of ChatGPT in terms of the general chatbot market. What is imperative is that we explicate what this era of conversational AI means for mobile apps and why it’s so cutting edge. The predominant factor is how much more accurate, comprehensive, and realistic conversational AI now is. Not only does the ChatGPT prototype adapt to the user in a way that naturalistically matches their own mode of communication, it’s more relatable and improves the UX. In analysis for Data Science Central about chatbots and ChatGPT, James Wilson says, “The API is so powerful that you never realize it’s a program speaking on the other end.” Already, this is building trust with users and completely disrupting preconceived notions about chatbots and AI as we know them.
Unexpectedly, conversational AI also frees customer service team members to be more hands-on in delivering memorable, disruptive customer experiences. While the focus has been about how chatbots automate customer service, with more people turning to apps for all kinds of online activity from shopping to telehealth, the success of this AI may promise creativity and a focus on the user experience. Conversational interfaces, inclusive of ChatGPT, argues Ryan Bennett for CMSWire, are a catalyzing force. Bennett asserts, “AI-powered services have steadily been improving in the background over a number of years, and the recent viral nature of ChatGPT means that more of us — and crucially senior management — are now more aware of how much AI has evolved and its relative potential.”
Up until now, greater scope for specialized service hasn’t been possible due to high customer demand and reduced budgets; this has been an even more pronounced reality in the wake of Covid-19 and economic downturn in 2022. Gartner predicts that by 2027, just under five years away, chatbots will be the primary customer service channel for all organizations. From this standpoint, we can hypothesize that these changes aren’t necessarily for the worse and they could instead offer a pathway towards more meaningful customer and business connections. As the ‘AI race’ heats up, there are competing trajectories for what will happen in this space and for mobile app development.
Seven ways to update how your business is using chatbots and conversational AI in its mobile app development in 2023
The infrastructure around all tools can always be better. In the case of chatbots in mobile app development, there are many tactics available to improve the customer experience (CX), who are the main external stakeholders, on the receiving end of this technology. There is a need to manage the reality of customers expecting to have a poor experience by shifting their expectations and refining all facets of the CX approach of the business — not about ditching chatbots but instead switching gears to head towards personalization, strategy, and connectivity that targets problems and delivers solutions.
On the one hand, there is widespread adoption of chatbots, and statistics show that 45 percent of end-users prefer chatbots as the primary mode of communication for customer service activities. Nevertheless, on the other hand, there’s also compelling reasons for businesses to up the ante of their chatbot activities as data reflects the fine line between success and failure: 60 percent of consumers are less likely to remain a customer if they’re not able to transfer to a live agent, versus, 60 percent more likely to continue doing business if the transfer is seamless. The revealing takeaway here is the urgency around detail-oriented chatbot use and not relying on automation as a catch-all solution.
In this final section of this article, we’re going to cover seven ways businesses can revolutionize their approach to chatbots in their mobile app developments this year — no matter whether they’re already in use or it’s just the start of this journey:
- Base usage on industry-specific mobile app development
- Use data from existing work to inform how to use chatbots better
- Identify CX objectives and monitor performance
- Synthesize all dimensions of customer service strategy to retain customers
- Invest in customizing chatbots for mobile applications
- Make personalization a clear value proposition
- Review satisfaction metrics to rework and relaunch chatbots as needed
1. Base usage on industry-specific mobile app development
Firstly, let’s talk about industry-specificity. There is no successful catch-all approach for using chatbots: profitable and engaging outcomes require focused use. This starts with industry norms and what’s happening in the market.
A main point of media and expert discourse around chatbots is how the use varies between each industry niche of conversational AI in apps. In mobile app development, the main players are E-commerce, Real Estate, Human Resources, Healthcare, Manufacturing, Travel and Hospitality, Education, and Insurance. Of these industries, needs vary based on just some of the following:
- Scale of customer enquiries and service norms
- 24/7 enquiry management and lead generation
- Sales funnel and sales conversion
- Resolving problems
- Providing high-level advice
- Personalization expectations
- Educational interactions
- Administrative, scheduling, and process support
- Data and inventory management
- Business 2 Business (B2B) stakeholder management
- Coordinating cross-platform support
Detailed, thorough strategies require market understanding, analysis of the industry and competitor profiles, and clearly-ideated objectives. From here, businesses are positioned to improve how they use their chatbots for their target customers.
2. Use data from existing work to inform how to use chatbots better
Chatbots are a boon for data collection both for personalized customer service and scaling up the way an app is used. Auditing the chatbots being used helps to identify what is and isn’t working while staying open to opportunities to improve and level up this tool. The chatbot also only works as well as the data behind it, so the CX should subsequently win users once data sources are reviewed then incorporated in updating the training of the chatbot.
Time should be adequately devoted to the task of reviewing existing work. This includes reviewing existing data logs from chatbot interactions with customers, logs from human interactions with customers, and other sources of customer feedback data from social media and more detailed feedback channels. Sometimes problems are missed and having diverse yet layered sources helps to identify patterns. It can also help to isolate anything small that can have big impacts, such as if customers have a common problem that isn’t being answered, a technical issue that makes them quit the app, or if the sales process is taking too long.
3. Identify CX objectives and monitor performance
Customers are at the heart of chatbot use and, along with the investment in the chatbot training, there should be the same level of CX-oriented planning. Smart Insights effuse that the CX on mobile should always be a goal right from the moment a user starts with the application. They say, “The idea here is to make the onboarding process as seamless, beneficial, and endearing as possible for the customer.” Both referring to existing data around what is working and referencing the growth outlook for the business will contribute to designing these objectives.
Once CX objectives are established, designed, and deployed, then performance should be monitored. We explain in point 7. the relevance of reviewing satisfaction metrics. It’s important to note that customers are human and the performance will involve the assessment of both qualitative and quantitative metrics. Extrapolation will be much like point 2. wherein gaining insights about the CX involves digging in and exploring a wide-reaching volume of factors that are negatively influencing or compromising how the user engages with chatbots and the app at large.
4. Synthesize all dimensions of customer service strategy to retain customers
A popular albeit complicated myth about chatbots is that they are replacing customer service. Reports show that belief and reality of this is often contextual for customers depending on whether there is a wait involved with speaking with a live representative or if they are just seeking an answer via an available support channel. When customers are seeking assistance, they need a selection of avenues for getting help and, if there’s a problem, receiving resolutions.
As with many interactions, a key strategy is managing expectations from the outset of a customer’s interaction with the organization. Transparent, supportive communications about what the customer service infrastructure is in an app sets businesses up for positive interactions. Customers can be retained if they know what to expect with the lay of the customer service land. Protecting the CX with an outline of the levels of support — e.g. chatbots, service representatives being available at set times, requesting follow-up, and prompts for feedback — achieves an infrastructure that emphasizes customer needs being a priority. This frees the user to customize their support from the outset, too.
5. Invest in customizing chatbots for mobile applications
Customizing chatbots is as urgent a step as investing in the conversational AI. Put simply by Allen Bernard for CMSWire, “Even if the chatbot is doing nothing but supplying simple responses to simple queries such as “What time do you open?” the chatbot will still require your organization to provide those answers.” Just as we have already identified the use of data to customize the customer service chatbot features, the chosen chatbot — regardless of how good the provider is — needs to be prepared for the business using it and for the unique user context.
This needs to be detailed from a number of foundational points:
- Business information
- Customer profile
- Seasonal or changing data
- Domain ontology
- Foundational language training
- Integration with the application UX
There is no set-and-forget with chatbots particularly when the planning and building makes the performance of conversational AI functions worth the investment. Just as we have referenced the CX as being part of value generation for businesses, a customized chatbot is an asset as well.
6. Make personalization a clear value proposition
One unique selling point of robust conversational AI and chatbots that doesn’t get a lot of airtime is that they offer all of us a personalized UX. In customer service terms, the chatbot — and especially the infamous ChatGPT — is using machine learning to adjust its interactions with each person based on their unique inputs. McKinsey found that personalization “matters more than ever” in a post-pandemic climate and that companies that grow faster drive 40 percent more of their revenue from personalization than their “slower-growing counterparts”.
We’ve unpacked the need to communicate the customer service arms in the User Interface (UI) and it’s a sound choice here, too. Using the classification of “personalization” is an endorsement of the business’s belief in chatbots as one of their customer service modes. It has an informational influence as an explainer of the technology and equipping customers to authoritatively opt for their preferred service arm. Rather than obscuring the technology in use, celebrating its value improves the CX across the board.
7. Review satisfaction metrics to rework and relaunch chatbots as needed
The final way for businesses to improve CX is through meaningful review and maintenance processes. Chatbots are the support for businesses that then carries over to supporting their customers throughout their algorithmic data collection activity — both in active customer engagements and in passive data sets derived from user activity. This data helps build and customize the chatbots and it can help with understanding the strengths and weaknesses of the application UX for customers.
Revision of processes is paramount to the success of all businesses. Investigating and interrogating stakeholder satisfaction metrics should never be shied away from and chatbots make this easy, to a certain extent. Practically applying assessments of data and reviews as metrics to gauge how a chatbot is performing can fortify the business offering while progressively upping the standard of the conversational AI.
In conclusion revolutionizing the approach to chatbots is a process that needs businesses and mobile app developers to use a fine-tooth comb. At the moment, many companies have live customer service representatives using chatbots as part of their resolution toolkit and they are delivering an attractive CX. This, more than anything, should be the guide for all businesses as Zendesk found, in a 2021 study, that 75 percent of customers will spend more with a company that offers a good customer experience!
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