Chatbot Case Studies: A Showcase of Massive Improvements

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Credit by Chatfuel

We have witnessed time and again how chatbots have completely revolutionized the digital customer service space. The numerous success stories highlight the differences before and after using chatbots. While there are quantitative discussions of specific benefits, there is also plenty of anecdotal information backed up with robust analytics data to prove, without a doubt, how powerful a tool chatbots can be.

And, of course… chatbot case studies. These reports greatly help us form a vivid understanding of how chatbot (system) benefits actually work to aid businesses and organizations. After all, they are often utilized by providers themselves as a way to promote their brand and field of expertise directly.

Some even give hints of what’s in store for chatbots for the next few years ahead.

DECEN Muebles Infantiles: Only 20% of Sales NOT from Chatbots

insights into Chatbot Case Studies
Credit by DECEN Muebles Infantiles
  • Chatbot Provider: Chatfuel (case study)
  • Industry: Children’s (infant) furniture online retailer
  • Specific Result Achieved: Direct Facebook product browsing and content promotion
  • Main advantage(s) utilized: 24/7 availability, survey extraction

DECEN’s mission is to follow its safety-beauty-sustainability design with its baby products. Unfortunately, the same thing cannot be said for its (Facebook) Messenger inbox, which became uncontrollable as its business grew exponentially.

Using a chatbot to redirect questions definitely was the correct and standard path to take. However, Chatfuel wanted to take the convenience level one step further. Instead of just being answered by the bot, users can directly browse for products in Messenger itself using intuitive text and natural language-based commands. They also added a sprinkle of limitation, preventing unrestricted user input so that customers wouldn’t get distracted by negative bot answers.

Today, DECEN’s reputation is as robust as ever, with constant giveaway promo events being used as the main centers of information gathering. Their number of positive leads has also significantly increased, as expected, leading to a whopping 80% of its sales generated entirely by its chatbot system.

Tryg: Nearly All Internal Chat Queries Now Handled by Chatbots

a rescue ring
Credit by Tryg
  • Chatbot Provider: Boost (case study)
  • Industry: Insurance
  • Specific Result Achieved: Speedy complex issue resolution via reduced load.
  • Main advantage(s) utilized: (optimized) staff management, interactive data resource

Tryg, a Scandinavian insurance company, began a project called Rosa in 2018, with the cooperation of Boost.ai. The ultimate objective? To build a tool that would eliminate many of the unnecessary layers within its internal operations.

In terms of solving queries, the success story is more or less the same as all other case studies we have seen prior. Processing becomes automated, and this allowed human agents to solve more complex issues with better focus and prospects.

However, when it comes to personalizing the service itself, Rosa became a very powerful tool for its employees. It is now essentially considered to be a smart hub of information within Tryg itself. New updates don’t just come in cold and dry pieces of text, but are given color and life. It even comes with bonus suggested actions and other information to boot! The internal virtual agent became as much of an access convenience to the ones who deployed it.

RapidMiner Case Study: 100% Chatbot Management

UI for Chatbot Case Studies
Credit by RapidMiner
  • Chatbot Provider: Drift (case study)
  • Industry: Data Science Software
  • Specific Result Achieved: 66% task handling, 33% human agent turnover.
  • Main advantage(s) utilized: Leads filtering, 24/7 service, total chatbot takeover

RapidMiner, due to the nature of the services it offers, immediately concluded that users don’t actually visit its website to look around and browse. Rather, for the most part, it is almost always specifically to answer a query.

So its management came up with a very bold decision: to build a chatbot platform that would handle every single fill-out form submission, completely and independently on its own. People would visit the site, answer pre-made forms guided by chatbots, and those that are deemed “potentially viable” would then be continuously sent nurturing emails. This information exchange then eventually leads to an actual human agent or representative, depending on the likelihood of a lead becoming a hit.

The result of a 100% frontline chatbot management? According to Drift at least, 25% of RapidMiner’s open sales pipeline became influenced directly by the chatbot platform, equivalent to about 4,000 actual leads within just half a year.

Perfecto Mobile Case Study: Website Conversion Rate Up 400%

Perfect Mobile an example of one of many chatbot case studies
Credit by Perfecto Mobile
  • Chatbot Provider: Drift (case study)
  • Industry: Internet-based app testing platform
  • Specific Result Achieved: Lead generation rate grows from 6% to 20% in only six months.
  • Main advantage(s) utilized: Human resource reallocation, process streamlining

Perfecto Mobile had the “perfect” business plan: to provide automated testing for mobile and web apps set to compete within their respective business spaces. The problem was that their sales development representatives (SDRs) were handling too much user traffic without getting significant leads. Specifically, the leads that the business was supposed to be dealing with weren’t handled properly, while users outside the company’s target audience kept flowing in.

After implementing a chatbot in tandem with a shift in website information focus, Perfecto was able to get incremental improvements over the following months. Its SDRs no longer have to handle queries one by one, but only those that are very highly likely to generate a sales lead, because the chatbots have effectively filtered the list and streamlined the process. The rest of the other users are “routed” outside the system, either by quickly resolving a query or analyzing the user’s representative service size.

Charter Communications Case Study: ROI Increased Five-fold in Half a Year

Worker fixing telephone pole
Credit by Charter Communications
  • Chatbot Provider: Next IT (case study)
  • Industry: Telco services (Cable, Internet)
  • Specific Result Achieved: Doubled processing speed, resulting in exponential ROI.
  • Main advantage(s) utilized: Total chatbot takeover (for baseline tasks)

Being the fourth-largest cable operator in the U.S., Charter Communications started quite early in developing business infrastructure to establish broadband internet services at the beginning of the 21st century. Within the last decade, however, the long-time company struggled to handle very simple queries. More than 38% of its monthly online chat queries were something as simple as a forgotten account detail, and this was funneled within the company’s relatively limited human-operated customer service.

True to their design, chatbots became the simplest solution for all of these super simple queries. Not only were they able to preserve the internal chat system already in place, but they were able to use it directly as a platform for the chatbots to quickly and accurately filter out these ridiculously easy questions.

As a bonus, the chatbots could also consistently solve them 50% faster than any human operator. All these points combined helped the company’s ROI to skyrocket through reduced costs in maintenance, labor, and system operations.

Chatbot case studies: 3D Mats 999% Return on Ad Spend

  • Chatbot Provider: GoSky AI (Chatfuel Agency Partner) (case study)
  • Industry: Car accessory online retailer
  • Specific Result Achieved: Repetitive inquiry rerouting, Facebook ad boost
  • Main advantage(s) utilized: FAQ automation, direct bot linking

Taiwan-based 3D Mats was faced with a serious problem when its Facebook ads did not achieve their expected success. This was further compounded by the fact that the company itself did not have technical knowledge of its ideal client base, making it even harder to market these ads accurately.

GoSky AI proposed a direct and bold solution: to introduce a product-recommendation flow that would be used in tandem with their automated FAQ department. Information collected through this system would then be redirected onto the AI engine. This would adapt and evolve to produce better-targeted content, collecting even more data from users to adapt again and again.

Once the company had enough data to ascertain its target customers’ range, manual adjustments could then be made to the chatbot. After some time, the chatbot was able to reduce repetitive inquiries by 70%, and the major information collecting boost provided a whopping 999% return on ad spend rate annually.

Why Even Try to Prove Chatbot Efficiency with chatbot Case Studies?

The overwhelming figures provided by these case studies serve to prove just how revolutionary chatbots can be on all kinds of applications. But, even at a theoretical level, simply understanding how chatbots work already gives us an idea of their significant benefits.

So, why do we need proof such as these?

The answer is simple: quantification. Explaining the strategic benefits does help us get a grasp of the industry’s potential. But until we see actual results, the extent of these advantages remains a speculative figure. In addition, chatbots have different implementations for different businesses, despite how similar the base design may seem to be. As such, the final efficiency rate could wildly differ.

On a less formal side, seeing all these case studies also helps us know exactly how the chatbot was used, and which services were implemented to great effect. It could serve as a reference to give a clearer picture of how your ideal chatbot should function within your business or organizational system.

All sources are provided as links within the article.

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