Last updated: The move from mobile apps to chatbots

The move from mobile apps to chatbots


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What’s all the buzz about bots? As an overall trend, mobile application downloads and number of apps people use per day are declining while there’s an overwhelming increase of chat application downloads and usage. Many companies, such as Facebook and Microsoft, see an opportunity in this space for businesses to communicate with users on a messaging platform.

How are chatbots going to be applied to the enterprise space? Will chatbots change the way we design experiences? The goal for enterprise chatbots is to assist users by aiding in solving complex business scenarios while fostering efficient processes.

But how will users trust and tolerate chatbots?

Trust for bots

There must be a level of trust from users in order to maximize the benefits of bots. Why is this the case? Because users will be more likely to share and seek information from bots while trusting the credibility of its content. Additionally, users will be more engaged in the content and the bot can become the first line of contact for information.

In the enterprise space, bots will be handling crucial and confidential information that may heavily influence the success or failure of a business.

Users will need to trust bots to aid their decisions, submit requests, and other expectations in various business scenarios. Contextual information can also increase trust.  As trust increases, bots will be handling more important content and users will rely on it more.

Trust is deep rooted from a variety of personal traits when it comes to trusting another human being; such as having similar attributes, risk tolerance, relative power, and capability. Does this apply to chatbots as well?

I ask this because users will know or be aware that the bots are not human, but will they expect the same sort of qualities or evaluate the bot with the same criteria as it would to another human being in order to trust?

These are important questions to consider because enterprise bots will be handling matters that may affect a user’s productivity and career based on a sole decision, which means they will need to rely on the bot to give them accurate and contextual information. For instance, a sales associate will be able to receive alerts or suggestions on new leads based on historic and contextual market data.

The associate needs to trust the bot in order to accept its suggestions and decide what to do. Consequently, a user arguing, “The bot gave me false sales reports” may be difficult to convince others because people will most likely see the bot as an accurate system with little potential for errors.

On the other hand, humans are probably more likely to make errors. A bot can consolidate business data, historical statistics and productivity much more quickly than a human being. Once trust is established between the bot and user, it could be highly beneficial for enterprises to reach increased productivity and profitability.


How much are users willing to tolerate errors and limitations? This is a highly subjective matter because some will be experts to bots, trying to ‘break the system’, while others are satisfied with simple tasks and more tolerant to forgive errors.

Tolerance for each user is not easy to predict at the moment because it is too early to have enough data.

However, some research has shown that most users are satisfied with the tasks that the bots are meant to do with little to no intention of ‘breaking the bot’ (by asking unrelated or highly complex questions).

I believe the study of human behavior and interaction with chatbots will be increasingly popular and in demand in the next few years. It’s not a new concept, but it is new in the sense that users will be able to transition from using multiple mobile apps to using one messaging platform to handle all or most of their tasks.

Thank you, bot

Users understand and are aware that the bot is not human, but some still feel the need to thank them for their services. What could this mean? We still seek human interactions or behaviors because it’s in a conversational context.

Humans feel the need to react and interact with others (even if it is a bot).

This could be valuable information for how we shape and design conversations in enterprise bots because it can reveal underlying user needs.

Do users need bots?

It may be interesting to consider the way bots have been introduced to users. Bots were not necessarily driven by user needs, they surfaced from businesses introducing it to users. After speaking to several people who are not yet familiar with the concept of chatbots, it was interesting to hear their perspective.

They questioned why bots were necessary, and that they would be more likely to use it if it improves the way they perform tasks in their daily lives. Although this is just a small sample of potential users, it is important to consider existing perceptions of bots and how we can begin to change it as we introduce new chatbots.

Future of bots

User experience design for chatbots will be based on communicative interactions between users and bots. Bots may have different types of personalities or purpose, but users will nevertheless expect a level of intelligence and capability to accomplish tasks that it claims to be able to do.

If we focus on the bots capability and ensuring that it is able to properly serve the purpose that it claims to do, it will most likely be able to deliver positive user experience. This is a developing relationship that will be interesting to observe and learn from as chatbots become increasingly accessible to the users’ in daily life. There is no doubt that bots will be increasing in the near future.

At this point, we may not be able to predict exactly how users will behave or react to them, but it will be interesting to observe and learn about the developing relationship between bots and users regarding trust, tolerance, and overall communicative interactions.

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This post originally appeared on Forbes SAPVoice and is republished here with permission.

Editor’s Note: Post written by Shae Maeda, UX Designer, SAP

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