7 Call Analytics Platforms Using Machine Learning to Identify Caller Intent | Street Fight

7 Call Analytics Platforms Using Machine Learning to Identify Caller Intent

7 Call Analytics Platforms Using Machine Learning to Identify Caller Intent

 

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Long before merchants were tracking website clicks or social media shares, they were using incoming telephone calls as a barometer for the success of local marketing campaigns. Even today, with digital channels capturing the lion’s share of attention among local marketers, merchants still rank phone calls as the most important metric to gauge the success of their marketing initiatives.

What’s keeping inbound phone channels relevant is the injection of machine learning and custom modeling into today’s call attribution platforms. Providers are introducing adaptive learning technology to categorize data and generate increased insights from inbound phone calls, giving merchants the ability to better understand what types of telephone calls are being driven without actually listening to recorded calls.

Here are seven examples of call analytics and attribution providers using advanced technology to identify caller intent.

1. DialogTech: Leveraging machine analytics to categorize calls
DialogTech is a call analytics and optimization platform that’s using adaptive, machine learning and custom modeling to categorize data and insights from inbound telephone calls. DialogTech gives marketers a way to identify caller intent and new trends, and more accurately predict call outcomes. Marketers can also use DialogTech to better understand what types of calls are being driven by their online and offline campaigns — for example, good leads or bad leads — without actually listening to any recorded calls.

2. Marchex: Attributing inbound calls to keywords or impressions
Marchex is a mobile advertising analytics firm, but the company offers a call analytics component that uses patented technology to inform marketers of which ads, campaigns, and channels are generating the most qualified inbound calls. In addition to attributing phone calls to channels or ads, marketers can attribute calls to keywords or impressions. Marchex’s conversational analytics technology automatically visually maps, classifies, and scores every inbound call, as well, without requiring calls to be recorded.

3. RankMiner: Predictive voice analytics
RankMiner uses predictive voice analytics software to measure voice-based emotions and behaviors. It then takes these measurements and uses them to predict successful business outcomes. Designed primarily for call centers, along with inside sales teams and customer service, RankMiner listens to 100% of a team’s calls and lets users know which clients or leads are with pursuing based on the language that they use. RankMiner has been designed to ignore words and focus on “emotional behavior and tone,” and it dynamically updates itself with validated results, so the predictions that RankMiner generates become more accurate the longer an organization uses the software.

4. Invoca: Identify effective sales messaging on inbound calls
The call intelligence vendor Invoca essentially optimizes inbound telephone calls using the same automation concepts as companies use for website clicks. This automated intelligence enables marketers to better understand which campaigns are driving the types of calls that actually lead to sales. Marketers can also automate the experience for callers and optimize their efforts to drive more qualified calls. The company’s Invoca Signal product uses technology to identify the sales messaging that closes deals and even determines when competitors are mentioned on a call.

5. VoiceBase: Applying big data to detect important events
Although VoiceBase is primarily a provider of speech APIs, the company has an Insights product that identifies valuable events and uses the information to automate business processes. VoiceBase applies big data and machine learning to automatically detect any event that’s important to a business. VoiceBase utilizes callers’ preexisting “call tags” to generate volumes of data defined by speech, context, tone, and vocabulary. This data then goes into a neural network model that differentiates between events. Once the models are completed, businesses can send calls through the VoiceBase API and the platform will detect the presence or absence of each event.

6. ResponseTap: Call-based marketing automation
ResponseTap is a call-based marketing automation platform that provides organizations with the information they need to make data-driven decisions about their inbound marketing efforts. Dynamic call routing routes calls according to which Adwords campaigns users click from. ResponseTap also has a call benchmarking feature that evaluates calls based on their length, since the duration of a call can be an indication of its quality. By enabling visitor-level call tracking, ResponseTap believes marketers should be better positioned to improve the effectiveness of their campaigns and also attribute ROI more accurately.

7. Call Box: A human element within call analytics
Call Box is a call tracking and marketing analytics vendor that provides its clients with ways to increase the effectiveness of their campaigns. Businesses place unique phone numbers on each of their listings, and Call Box tracks all of their phone calls, and then employs humans to listen to those calls. Call Box believes that humans are more effective and accurate at call evaluation and lead scoring than automated solutions. Call Box’s team evaluates how calls are handled and automatically reaches out to staff members who appear to be struggling. Call Box then tracks the follow up effort to get missed opportunities back in play.

Know of other call analytics platforms using advanced technology? Leave a description in the comments.

Stephanie Miles is a senior editor at Street Fight.

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