Ever since the mobile revolution began, we have been able to collect huge amounts of data. In fact, in just a single minute, there are 4,166,667 Facebook likes, 347,222 tweets, and 284,722 Snapchat snaps generated. In a full day, 2.5 quintillion bytes of data is produced.
Large volumes of data can be a tremendous asset to businesses. This is because businesses can use the data to get insights into consumer behavior, the market, competing products, their own company, and much more. However, a company can generate so much data that it is unable to effectively use it all. This is where chatbots can be extremely helpful.
A chatbot is a tool that is capable of handling complexity. Chatbots can sift through large volumes of data quickly and provide real-time, effective use of that data. In other words, chatbots can help to bring order from chaos. For example, chatbots can do things like answer customer service questions, scan many local restaurants to help you book dinner reservations, check sports scores, and order flowers.
Chatbots can be extremely helpful for many businesses. In fact, using a chatbot effectively can be a strong competitive differentiator for a company. However, some businesses stand to gain much more from the use of chatbots than others. Here’s a look into how a company’s data volume affects the usefulness of chatbots.
Companies with large amounts of data
Companies with a high level of data can benefit the most from chatbots. Such companies include major insurance companies, credit card companies like American Express, or others that gather tremendous amounts of data. The reason why these companies can benefit the most is because the larger a company’s data volume is, the more opportunity chatbots have to help the business.
Without chatbots, employees at high-data companies may have trouble keeping up with and effectively using the data. However, a company can implement chatbots to handle business functions that involve scanning through these large levels of data.
For example, an electronics manufacturer could put a chatbot on its website that can help with complex customer service questions. Such a chatbot could quickly search through hundreds, or even thousands, of models and products, and provide specific individual details about each product. When you consider that the process of answering these questions may have to be repeated hundreds, thousands, or even tens of thousands of times in a year, you can really see how a chatbot can be useful for companies with large amounts of data.
Chatbots can also be used internally by companies to analyze key data that the company collects. The chatbots can scan the data in seconds, thus preventing employees from having to take ages to dig through it. Using chatbots in this manner can help companies arrive at key conclusions that can help market research, product development, competition analysis, and many other vital tasks.
Companies with small amounts of data
Companies with small amounts of data have a considerably reduced need for chatbots. After all, the primary purpose of chatbots is to help companies use their data more effectively. So if a company is not collecting significant levels of data, then a chatbot is not going to be able to help very much at all.
Companies that do not collect large amounts of data may include small retail stores with only a few products, companies that do not have a large online presence, or companies that don’t use the internet for their business at all.
If these companies do collect some data, a few employees may be able to easily make use of it. For example, a small retail store may keep a list of its most important competitors. This data may be used by an employee without the assistance of a chatbot.
Chatbots are an incredibly exciting development in the tech world because they can potentially help companies save a lot of money and can speed up many business processes. However, chatbots are substantially more helpful for companies with higher volumes of data than those with smaller volumes. The amount of data that your company needs to collect and analyze in order to differentiate itself determines whether or not you should look into chatbots.