{"id":26082,"date":"2026-08-04T16:36:54","date_gmt":"2026-08-04T16:36:54","guid":{"rendered":"https:\/\/www.mediashower.com\/blog\/?p=26082"},"modified":"2026-08-04T16:40:05","modified_gmt":"2026-08-04T16:40:05","slug":"ai-assistants-for-websites","status":"publish","type":"post","link":"https:\/\/www.mediashower.com\/blog\/ai-assistants-for-websites\/","title":{"rendered":"AI Assistants for Websites: Benefits, Case Studies, and Best Practices"},"content":{"rendered":"\n

Michaels<\/a> is onto something.<\/p>\n\n\n\n

The arts and crafts supply retailer says visitors who use its \u201cAsk Mike\u201d AI assistant convert at more than twice the rate of visitors using traditional search<\/strong>. <\/p>\n\n\n\n

The assistant handled 75,000 conversations during its early rollout, and 27% of those interactions led to a product click or add-to-cart action.<\/p>\n\n\n\n

The numbers<\/a> are early and company-reported. But the behavior shows that customers are expecting websites to do more than retrieve information. They want help choosing, troubleshooting, and completing the task in front of them.<\/p>\n\n\n\n

And when companies give an AI experience to their customers, the customers are more likely to buy<\/em>.<\/p>\n\n\n\n

That shift changes the website journey from \u201csearch, browse, and compare\u201d toward \u201cask, clarify, and recommend.\u201d<\/p>\n\n\n\n

\"Ask<\/figure><\/div>\n\n\n\n

Why Are Website AI Assistants Replacing Search?<\/h2>\n\n\n\n

Website search remains useful when customers know exactly what they need. AI assistants create a different kind of value for people who know the outcome they want but still need help reaching it.<\/p>\n\n\n\n

Search retrieves<\/h3>\n\n\n\n

A traditional search begins with a keyword.<\/p>\n\n\n\n

A Michaels customer might search for \u201cfloral fabric,\u201d \u201cblack balloons,\u201d or \u201csilver tablecloth.\u201d Each query returns a separate set of products, leaving the customer to assemble the larger solution.<\/p>\n\n\n\n

That works when the shopper already understands the project and its requirements. It creates friction when the shopper has only a goal, such as planning a space-themed birthday party on a specific budget.<\/p>\n\n\n\n

Assistants clarify<\/h3>\n\n\n\n

Ask Mike lets customers describe the whole project. The assistant can ask about the occasion, colors, materials, budget, and other requirements before recommending a coordinated set of products.<\/p>\n\n\n\n

For example, they might say, \u201cI need a pattern and blue yarn for a baby blanket for less than $50.00.\u201d<\/p>\n\n\n\n

Michaels says they categorize products by project, and assistant users frequently add core supplies and finishing touches during the same session. <\/p>\n\n\n\n

Search helps customers find an item, but conversation helps them think through the project.<\/p>\n\n\n\n

The same need appears in B2B environments, although the stakes look different. A customer may be trying to solve a login problem, answer a client\u2019s urgent question, or complete a time-sensitive task inside a complex software system.<\/p>\n\n\n\n

They don\u2019t need another list of links. They need help moving forward.<\/p>\n\n\n\n

The website learns the customer\u2019s language<\/h3>\n\n\n\n

For decades, websites have required customers to learn the company\u2019s language.<\/p>\n\n\n\n

Visitors navigate departments, product categories, resource centers, and help-center taxonomies. They translate their needs into the terms the website recognizes. Sometimes they succeed. Sometimes they try six slightly different searches and quietly leave.<\/p>\n\n\n\n

AI assistants reverse that relationship. Instead of forcing customers to think like the website, the website learns how customers describe their problems.<\/p>\n\n\n\n

That gives us a useful way to describe the new journey.<\/p>\n\n\n\n

\"Traditional<\/figure><\/div>\n\n\n\n

The search box became standard because every website had information visitors needed to find. AI assistants will become standard because every website has customers trying to accomplish something.<\/p>\n\n\n\n

Do Website AI Assistants Improve Business Results?<\/h2>\n\n\n\n

The early evidence is promising, although companies are measuring different outcomes.<\/p>\n\n\n\n

Here are some additional case studies that show promising early results.<\/p>\n\n\n\n

Sticos resolves<\/h3>\n\n\n\n

Sticos<\/a>, a Norwegian compliance-software provider, serves accounting and auditing professionals who depend on accurate, timely guidance. Many incoming questions are repetitive, including login issues, password problems, and basic product questions. Their urgency remains high because the professional asking often has a client waiting.<\/p>\n\n\n\n

Sticos reports<\/a> that its customer agent handles 41% of incoming support<\/strong>, beating the company\u2019s 40% target. The assistant has achieved a 91% chat-deflection rate<\/strong> and a 75% chat-resolution rate<\/strong>.<\/p>\n\n\n\n

With routine questions handled automatically, the human team has more room for proactive customer-success work and conversations that require judgment.<\/p>\n\n\n\n

Bitfocus accelerates<\/h3>\n\n\n\n

Bitfocus<\/a> operates software used by organizations coordinating shelter, outreach, and housing services across the United States. Its users may need answers outside standard West Coast support hours while working directly with people who need immediate assistance.<\/p>\n\n\n\n

The company\u2019s AI customer agent provides round-the-clock help through its help center and in-product chat. Bitfocus reports<\/a> that the assistant deflects 40% of incoming tickets<\/strong>, has reduced overall time-to-solve by 65%<\/strong>, and has generated roughly $300,000 in savings<\/strong>.<\/p>\n\n\n\n

Ticket volume has also leveled off as the company\u2019s customer portfolio has grown. Support teams feel that kind of scalability directly: customer growth no longer creates the same proportional increase in demand.<\/p>\n\n\n\n

Measure whether customers move forward<\/h3>\n\n\n\n

Michaels, Sticos, and Bitfocus are tracking different metrics, but each one points to the same underlying question: Did the customer get closer to a satisfying outcome?<\/strong><\/p>\n\n\n\n

For Michaels, that means finding the right collection of products and moving toward purchase. For Sticos, it means giving a professional a timely answer so they can return to client work. For Bitfocus, it means helping a frontline worker resolve a software issue without waiting overnight.<\/p>\n\n\n\n

Conversation volume alone tells us very little. A thousand conversations that leave customers confused are hardly a triumph.<\/p>\n\n\n\n

Choose the measure that best reflects the job you gave the assistant, then watch what happens after the conversation. Did the customer click, buy, resolve the issue, request a quote, or move to the next step?<\/p>\n\n\n\n

The right measure depends on the job you gave the assistant. <\/p>\n\n\n\n

How Do You Launch a Website AI Assistant?<\/h2>\n\n\n\n

At Media Shower, we\u2019ve been building custom AI assistants for enterprise customers for several years, with thousands of customer conversations under our belt. (Learn more about our services here<\/a>.)<\/p>\n\n\n\n

We\u2019ve found the strategic work lies in choosing the right task, supplying reliable knowledge, defining success, and improving performance after launch. Here are some of our best practices.<\/p>\n\n\n\n

Pick one task<\/h3>\n\n\n\n

Start with a customer task that appears frequently, carries business value, and requires more guidance than a static page can provide.<\/p>\n\n\n\n

Good starting points include:<\/p>\n\n\n\n