How to apply chat- & voicebots to your business

5 min

The global intelligent virtual assistant market is expected to reach USD 19.6 billion by 2025, at a CAGR of 35.4% between 2019 and 2022. As we mentioned in our previous blog, it’s not a matter of if, but when chat- & voicebots will transform your business. Given the pace of developments in Artificial Intelligence (AI), Natural Language Progressing (NLP) and Machine Learning (ML), it’s vital to jump on board this high-speed train and start with the implementation of intelligent automation across your company.

When organizations start new projects they generally need a solid business case with valid assumptions to allocate the required capital and resources. Since this technology is so new, for most corporates it might be too early to calculate a business case with a clear ROI on chat- & voicebots with great confidence. The many use-cases for B2C or B2B shared in the market are a good general guide, but the question corporate executives and their direct reports are asking is: how do we make the business case for chat- & voicebots for our specific situation?

In this blog, we’ll give you a 6-step plan to start exploring the value of chat- & voicebots for specific use-cases in your business and to create a business case for scale. Traditional ROI calculations don’t necessarily reflect the full gains to be made from chat- & voicebots, so we suggest a slightly different approach based on the benefits and value-add of new technological innovation.

Six steps to explore the value of chat- & voicebots for organizations

1. Select a company internal or external process with high human interaction

The easiest example for calculating the ROI on a chatbot’s business case is replacing part of your customer support with this technology. Since customer support involves a lot of human interaction with a clear price tag (human salaries), it helps you calculate the savings for every interaction you can automate. Chat- & voicebots can be deployed effectively in marketing and sales but also in ‘internal customer processes’ like HR support and IT help-desks. It’s slightly harder to determine the direct cost for HR and IT since most of these professionals are not dedicated to simple interaction tasks. Therefore start by selecting high-frequency processes based on intensive human interactions, complex time-consuming processes, or interactions that have a high impact on growth, retention or revenue.

2. Investigate the complexity and current user-satisfaction

In order to set a baseline and select the processes to start with, commission the data- or process analysts in your company to analyze the last internal or external user-interactions over 6 to 12 months. Try to discover the patterns of easy versus complex questions and how they can be clustered, starting with the processes that create most value. For example, a sales manager’s request for 20 reports from a department may take 8 hours to deliver. When that process is automated, it can answer a wide variety of similar questions from multiple employees within 30 seconds. The value can be expressed not only as more rapid and accurate data analysis but potentially more rapid sales conversion and better use of the sales team’s time. Make sure to measure current user-satisfaction levels, as changes in these processes might impact the overall satisfaction of your products, services or brand.

3. Create hypotheses and run tests and proofs of concept

To measure the success of a proof-of-concept and predicate how to implement this at scale in your organization, you need to create hypotheses that can be measured objectively. State the problem you want to solve and set clear targets or KPI’s for the tests. What do you want to improve and by how much? How much time and resource are you prepared to invest in designing and running the tests? How will you measure results and when is it a success? This approach is similar to the Growth Hacking methodology. Use the Strategyzer test card, for instance, to document the steps to take, then just start testing and improving step-by-step.

4. Calculate your business case based on the value-add and benefits

After the first test, you’ll have more data on which elements are working and will create value for your organization. At this relatively early stage, it’s also useful to consider the return on chat- & voicebots in terms of impact and value alongside a strict cost/gains formula to gain a better view of the full benefits for your organization. As Eric Ries, the creator of Innovation Accounting, puts it: the value that innovation creates is more than financial metrics. Think not only in terms of cost savings and income generation but also customer satisfaction, employee motivation, improved sales qualification, and efficiencies in your business.

5. Calculate the business value at scale

In order to extend to value and maximize the automation value-add within the whole organization, it’s key to calculate the business case at scale before you decide whether to implement it further. Be aware that a chatbot or Virtual Assistant solution implemented successfully in a specific corner of the business is no guarantee of success across the company. At scale new problems arise, like bot maintenance, continuous improvements, changing IT architectures, access management, governance, managing vendors, improving employee competencies and what McKinsey refers to as the ‘cultural effects’ of bots on operators—which could adversely impact the employee motivation factor. In the end, it will come down to balancing the elements that create value against the scale-up problems, work, costs, and potential (brand) risks. Only then can you make a proper judgment when to scale and to continue.

6. Take an orchestrated approach

chat- & voicebots have the power to transform organizations via intelligent automation and can create a lot of value. And as that transformation evolves, success will require you to move from digital experimentation and pilots to digital scaling of proven practices. While the delivery of digitization is still a CIO responsibility in most companies, it’s increasingly important to place organizational transformation in the context of a broader set of business objectives within all business lines.

Even when one or more divisions (for instance, IT, Finance, Marketing or HR) have jumped onto the high-speed train of chatbot and Virtual Assistant technology, there are still important questions for the leadership: where is that train taking the business as a whole? Are you on the right track and who’s in the driving seat?

To achieve maximum impact from the localized chatbot and Virtual Assistant success, the company must take an orchestrated and integrated approach to scale-up. At Blits we have developed a platform to help companies realize the value of chat- & voicebots and manage this transformation proactively. It’s a complex process that demands vision, ownership, and leadership.

It’s not a matter of if but when chat- & voicebots will transform your business. Given the pace of developments in Artificial Intelligence (AI) and Machine Learning (ML), it’s vital to jump on board this high-speed train and steer implementation across your company.

Our next blog will outline the steps for the controlled scale-up of chatbots and Virtual Assistants and integrated implementation. Using pilot cases, we will detail the impact on your organizational framework in 6 areas.

If you have questions about this blog or would like help and advice on making a start on chatbot & Virtual Assistant technology in your company, see how Blits can help you and contact us at this page.

 

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Blits Conversational AI Ecosystem

Blits is the low-code Conversational AI Ecosystem which combines the AI power of Google, Microsoft, IBM, Rasa, Wit, Amazon, Stanford and Nuance in one platform.

Use Blits to build, train and deploy chat- & voicebots at scale, for any type of use-case.

Focus on building a bot with the perfect tone of voice for your audience, and optimize the underlaying AI Technology later.

Always stay ahead of the competition with 'Blits Automate', giving your bots the latest combination of AI tech that fits your use-case automatically.

Reuse templates between bots, creating multi language/country/brand interactive communication on your existing channels (WhatsApp, Slack, Alexa, Twilio, Web, etc.)

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