Advertisements often promote chatbots in a way that showcases them as a modern, revolutionary technology that would significantly propel a business forward. The basic, fundamental concept of a chatbot is introduced as if it is an absolute operational necessity.
Internally, though, chatbots aren’t that much different from most other modern software. This is especially true when you consider that its standard structure is fundamentally the basic pillar of computer programming.
Of course, there are several distinctive elements and these form the basis of what a chatbot builder is integrally.
Feature-based Characteristics of Chatbot Builders
In terms of layout, there is not much that one will find in a chatbot builder that is different from typical software. Menu bars up top and side, lots of drag and drop elements, and an overview mode that lets you zoom in and out of your entire project.
As for things specific to chatbot builders, though, here are some of the feature-based characteristics you should take into consideration:
- Significantly less focus on coding, to the point that standard ones don’t even have any sort of coding whatsoever. At least not to the level of function and syntax complexity that you can typically find on more fundamental programs. It is easy to see how this “high-level” of software development benefits more casual users. But advanced multi-structural designs aren’t really as intuitive as they seem, and the advantages stem more from the time you can potentially save from eliminating manual coding, as opposed to just making it easier to use.
- Most builders have options for quick-response situations, for when a query only requires a very straightforward answer. In contrast to the standard workflow, this feature’s typical option only requires writing multiple separate entries for each possible question. As such, the graphical representation is much simpler, though priorities and information tiers can still be configured as usual. This feature is most popularly used for FAQ lists, since dealing with those types of questions doesn’t need further interaction, nor does it require potential redirects.
- Various notification tools, in-and-out of the builder, help facilitate accessibility and basic updating through easier setup methods. The entries for each interaction, and the parameters required to trigger the notifications, are configured even more separately than quick responses. Sometimes, automated actions can be assigned to these notifications, but the most important aspect of this feature is that it usually either reports updates on the client-side, or on the API-side.
- Task requests that need information input from the user can be executed without further steps involved. Lastly, call-to-action responses, where the chatbot is designed to provide a specific response to certain programmed situations immediately, are convenient when you need certain commands to be available on the platform. Configuring your chatbot using this feature is technically the same as when you configure notifications. But instead of just cutting the middle and informing the system of the update, an action is simply taken directly. Needless to say, this could also be integrated to involve multiple actions to a predetermined set of responses and actions.
- Test environments, much like a program compiler, are available and are necessities to see how your chatbot works on the fly. This is often integrated into your basic workflow menu, where each step (of the chatbot’s responses) may be checked and configured with a virtual version of the actual chatbot. Even though many builders feature no coding requirements, the source code may still be seen through these types of menus as well.
Structure of Chatbot Builders
When dealing with workflows, for most developers the question of what is a chatbot builder typically lies in how the chatbot itself makes its interactions. Because, while both are designed manually, their inner workings (for each subsequent response) can work very differently to the point that its complexity alone can determine the price of its overall services:
1. (Purely) Scripted Chatbots
As its name suggests, this type of chatbot mainly specializes in pre-written (pre-defined) scenarios for every single answer or response that it will do. As an automation tool, they are very invaluable in speeding up the information relay process, but are pretty much “dumb” in terms of active interaction. One can usually identify right away that it is a bot, as users don’t even expect it to have any sufficiently sophisticated response capabilities.
Applications where scripted chatbots are optimal:
- Very low-cost chatbot platforms – if you don’t need a particularly eloquent chatbot, a fully scripted chatbot can easily get you the minimum expected level of lead generation boost required.
- FAQ Hubs or Information Centers – instead of just writing off a long list of facts and figures, asking simple questions to a bot for these can be fast and efficient. They are relatively hassle-free on the development side as well.
- Very low to no expected interaction – for any type of application where the platform simply does not require full interactions at all. For example, issuing information relay commands over a collaborative messaging platform such as Slack.
- If a chatbot system mostly only offers pre-made responses – supporting all previous applications, purely scripted chatbots also work perfectly fine when the options do not allow users to freely type anything for a good portion of its “interaction”.
2. AI-based Chatbots
This is where the term “conversational AI” fits more perfectly than its broader term. AI-powered chatbots have, of course, become the norm over the past decade. They offer natural language processing (NLP), predictive systems, and adaptive capabilities good enough to interact in a significantly more human manner than any (purely) scripted chatbot. However, a proper distinction can still be made to those that mostly use AI-based interactions, as well as chatbots that use any of the practical principles of scripted chatbots.
Typical efficient applications of AI-based chatbots:
- Just about anything above low-cost and basic-interaction level – AI-based chatbots have steadily become the norm for a reason, which is due to their sheer adaptability. Costs have equally become reasonable as well, making it an irresistible offer for any business or organization that is large enough to require one.
- Fields and businesses that require the “human touch” – real estate dealerships, medical diagnosis, booking services, and other similar human interaction-dependent ventures need chatbots to be a bit more “sassy” to strike that sweet deal with their clients. A more convincing AI-powered chatbot should be able to negotiate its way through this process better.
- Any applications where natural language is the priority – speaking casually in human language, especially when it comes to internet lingo, requires flexible knowledge of expressive variations. In order to understand each version of roughly the same conveyed meaning, a good AI-powered chatbot is a necessity.
Naturally, to get the most out of your capital investment in chatbots, a combination of both would be ideal. Scripted responses for simpler tasks, revving up to more “intelligent” answers once interactions get complex enough (and learning from them for future interactions), then finally turning over to a human agent if the query is correctly deemed unsolvable by the chatbot.
The Hidden Specification: Support Systems
Generally, application considerations for chatbots usually start from the platform that they will be used on. Would it be a website-only platform? Does it have third-party support? What about popular social media platforms? Or is it just social media exclusive?
However, from the perspective of builders, support systems are arguably another very important determining factor. Just think, what is a chatbot builder for exactly with regards to your business? The builder, NOT the platform itself. Is it a tuned-up engine to drive sales up? A structured machine to optimize specific tasks? Or a beast of burden to streamline day-to-day operations?
For example, how long does it take for your or your development team to use a chatbot platform to its fullest extent? While a laundry list of options and features shows the chatbot’s huge potential, it won’t be fully realized until the developer actually uses them efficiently. Tutorials and samples are already a huge leap forwards in achieving such a goal. Suggestions can tip the balance towards mastery in a shorter amount of time just as well.
Another support system to consider is analytics. The amount and refinement of the platform-accumulated builder data is obviously a great tool in determining what works well and what doesn’t. This subsequently allows us to pinpoint areas of improvement, leading to even more open experimentation of ideas and implementations.
And lastly, customer service. This includes both business consultations and the simpler action of directly asking questions about the builder. As ironic as this may sound, the ease and convenience at which one can consult customer services also gives away the level of quality a chatbot builder can provide.