If your business generates a lot of incoming requests, you want to make sure each request is well-served to get tangible value. For example, conversion rates for some prospects double if an opportunity is followed up within 15 minutes after the request. Similarly, for service companies, a timely response to a breakdown report can avoid serious failures and related expenses.
WaveAccess develops and integrates machine learning-based information systems that automatically detect the type of an incoming customer request and assign it to a business process, saving time to process it.
During the 20-minute session with our technical architect we will examine your company’s current customer request workflow and have some optimization advice.
Book a discovery session
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17% conversion growth for flight booking platformWaveAccess has developed and delivered a lead scoring system that predicts the “quality” of a given lead based on its marginality and chance of deal closing. The most “quality” leads get high scoring and are processed by the sales team first. Download the case to find out how it took just six months for the company to get 17% growth in a highly competitive market of air ticket sales.
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Customer request automation for a service companyA service company gets up to 3000 repair orders daily. Most orders are categorized as warranty cases, which are low-margin. But in fact, up to 20% of warranty cases end up being the non-warranty type, which has higher margin. WaveAccess has developed and delivered a machine learning module that analyzes the order text and detects the case type and its category right at the input. Download the case and learn how a service company took advantage of digital transformation and grew its profits with a customer request processing system.
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Technical support ticket scoring systemThe customer gets a great number of questions regarding their products, that are redirected to the specific support subdivisions (Gold Members support, Support for individuals, etc.). Sorting and redirection were formerly done manually by an entire department. Read the case to find out how a machine learning module facilitated in speeding up and automating up to 90% of customer support operations.
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Skype calls and virtual screen sharing: we talk with our customers every day. Each week, project teams meet up for a weekly demo, sprint planning, and Q&A sessions.
80% of our customers are return buyers. Most of our clients recommend our services to their partners and colleagues.
A personal manager with fluent English will facilitate the communication between you and the development team. Teams use use customers' release management tools (Jira etc.)
Why? Good salaries, employee benefits, and a healthy working environment! We often send our staff for training and take pleasure in their progress.
You get transparent project management, along with a detailed risk map. You also get a list explaining project expenditure.
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