Conversational AI For Good: How Nonprofits Use New Tech
Over the past few years, chatbots have become an integral part of our lives when it comes to interactions with businesses. More companies rely on conversational solutions for better operations, lower costs and an easier recruitment process, so it doesn’t surprise anyone that chatbot market size is projected to grow to $10.5 billion by 2026, according to recent research. However, virtual agents can help organizations and projects that we usually do not view as tech-savvy. We’d like to explore how nonprofits and social responsibility projects, whose budgets are often tight, put Conversational AI to good use and make the most of it.
Conversational agents to the rescue
Even though it’s becoming more common for corporations to support nonprofit and charity organizations, most of them exist only because regular people like us make donations or help in some other way. So, nonprofits must establish proper communication with potential donors. And conversational agents can be of great help here.
For example, Upsala Circus, a nonprofit organization that comprises a professional theatre group, inclusive performance projects, and classes that socialize troubled or foster teens through performance arts, decided to get to know people who donate on their website. So they built a chatbot using chatbot builder Aimylogic by Just AI, which gathers information from the website visitors conveniently and securely: who they are, what kind of support they can provide, what kind of questions they have, also providing further instruction. Part of a long-term strategy, this chatbot will help the nonprofit make a donor segmentation and build communication properly. If someone is looking to be a volunteer, it hardly makes sense to explain how to donate money.
Getting more people to donate or make those donations recurrent requires reaching out across a variety of channels, and voice here seems to be one of the most natural ones. Alexa donations, for example, list 337 nonprofits — from American Childhood Cancer Organization to Children’s Miracle Network — that allow users to send money to charity via Amazon’s voice assistant. Some nonprofits create voice skills to encourage donations — for example, Need Help charity foundation that helps to raise funds for other nonprofit and charity organizations, launched a voice skill for Yandex’s voice assistant Alice (#1 voice assistant in Russia). Named “A Rouble a Day,” the voice skill enables users to choose from over 150 nonprofits and make a regular donation. To encourage smart speaker users to donate, voices of popular actors and media personalities explain why even such a small but regular sum can make a big difference.
Building communication with donors is also about being accessible across a variety of channels. Being in touch 24/7 is challenging even for regular businesses, but it’s especially tough for nonprofits as it requires extra staff. So, here’s when conversational agents and smart skills come into play — they can address the most frequent questions, navigate website visitors and offer necessary instructions. For example, NRDC uses an Alexa skill to help people avoid throwing out good food. The Save the Food skill offers advice on storing food to last longer, checking whether it’s still good, and even reviving food that’s past its prime. Among the users of Aimylogic chatbot builder, there is a nonprofit waste sorting project supported by IKEA named Rules of Sorting. They designed a social messenger chatbot to advise users on what kinds of plastic can be recycled, which recycling stations accept certain kinds of waste, and help users locate them.
Conversational agents can also become an interaction channel for those who cannot communicate verbally due to physical challenges. A great example here is a social responsibility project by professional haircare brand Indola, which is part of Henkel. Their chatbot enables hearing-impaired hairstylists to consult their clients online. There is also a chatbot called Mera Mitra, that serves as a companion for persons with disabilities, providing all kinds of the necessary information. Designed by two Indian developers, this chatbot is available in Google Assistant and Facebook Messenger.
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Why use Conversational AI?
Many charity organizations are successfully adopting conversational technologies: launching voice skills, chatbots, and even bespoke voice assistants. For those weighing the pros and cons of Conversational AI (CAI) projects, here are a few ways they can create value for nonprofits:
Automating communication
Full-time contact centers require a lot of resources, but nonprofits and businesses can efficiently use AI-powered conversational agents to automate communication with donors, website visitors, or just about anyone. Chatbots and virtual assistants can answer FAQs and address most common user queries, being available 24/7 across multiple channels.
Adopting new communication channels
Voice is yet another channel to communicate with the audience. So a skill for a voice assistant is a great way to tell people more about your organization or campaign, encourage users to donate, or conduct a survey.
Getting to know your audience
A chatbot can greet website visitors and start a conversation. This way, nonprofits can find out more about people coming to their website and build further communication more efficiently.
Reaching out en masse
Automated voice bots or text bots are crucial when you need to contact many people at once: be it a volunteer instruction, a new member registration campaign, or informing visitors of your charity event about the details.
Things to consider before starting a CAI project
First, it is necessary to understand that conversational AI agents are no panacea but rather a tool that, if used wisely, can improve certain processes over time. But, just like any tool, it needs to be created first and then constantly taken care of. Before you start working on this tool, please consider — what is it you want to achieve? Improve user experience, survey donors, or automate FAQs?
Think about the resources you have to create the bot — as it’s a full-blown IT project. Even when complete, the bot requires further training and honing — only in this case will it become truly smart and address most queries properly.
Another important thing is the bot’s efficiency because there are quite a lot of things that will define it and those need to be considered before any actual work is done:
What channels your bot will serve
A bot can be implemented anywhere — from WhatsApp to Facebook messenger, to Alexa. Some channels are quite similar, while for others you might need to create an entirely new UX scenario. Depending on the chatbot software you choose, you might need to create custom bots for every channel unless this tool allows for multichannel integration when you create a bot once and then deploy it across many channels.
What chatbot software you should choose
There are many kinds of chatbot software — from no-code visual bot builders to advanced platforms. It all depends on how much you’re willing to spend on your bot and the manpower you have at hand. Of course, the low-code chatbot builder options are great for short-staffed nonprofits, as such projects do not require a professional developer at the early stages.
Will you have the resources to continue training your bot
Even after your bot goes live, you’ll need to keep analyzing bot-to-users interactions to improve it. And there’s always something to improve when it comes to conversational agents. Launching a bot and forgetting it exists for a year, means you’ll have your time and money wasted.
How many topics your bot will cover
Even a small nonprofit will have many topics: donations, volunteering, to many other ways people can help the organization. There will also be topics that a bot is not supposed to address — usually, those requiring empathy — and should be able to transfer those to a human.
To sum it all up, conversational tech is advanced, diverse, and offers tools that require little to no coding skills. And, as long as a company understands what it wants to achieve with a conversational agent, it can start a CAI project on its own and then grow it evolutionarily.
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