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Supermetrics for Google Sheets is a powerful add-on that turns Google Sheets into a full-blown business reporting system for SEM, SEO, web analytics and social media. With this tool, you can: 1. Get metrics from multiple sources into Google Sheets. We provide integration for Google Analytics, Adwords, Facebook Ads, Bing Ads, Twitter Ads and dozens of other platforms listed below 2. Refresh reports automatically or by a click of a button. 3. Create professional-looking reports with our pre-made templates 4. Schedule automatic emailing as PDF, Excel, CSV or HTML, or give others access to your reports & dashboards. 5. Avoid Google Analytics data sampling and the 90-day limit of Google Search Console data
CallHub helps you schedule automated voice calls and SMS/text messages, integrates smoothly with user groups in your Google apps domain.
Limber is a cloud-based Content Marketing Automation platform, created for marketers to help them centralize disseminated content, structure and automate distribution across social media, measure their effectiveness using unified statistics and convert audience into sales-ready leads.
MonkeyLearn is an AI platform that allows companies to easily analyze text with Machine Learning. Customers like Clearbit, Segment and Drift are using MonkeyLearn to turn emails, support tickets, customer feedback, and documents into actionable data. You can easily classify texts by topic, sentiment or intent or extract specific data such as keywords, names, and companies. MonkeyLearn makes teams more efficient by automating business processes, getting insights and saving hours of manual text data processing. Text Classification Text classification models are used to categorize text into organized groups. Text is analyzed by a model and then the appropriate tags are applied based on the content. You can classify texts with custom categories or tags for sentiment analysis, topic detection, product classification, aspects detection and much more. With MonkeyLearn, you can use our library of publicly available classifiers and you can also make your own custom classifier for your own specific use case. Text Extraction Extraction models are used to extract data from text, that is, the result you are looking for exists within the text. The difference with extraction compared to classification is that in classification the result is an associated tag that is usually not present within the text, and therefore has to be predicted or deduced from the text contents. MonkeyLearn has different extraction models to extract different types of data: entities, company names, keywords, addresses, emails, etc. You may work with the extraction models publicly available to resolve your particular problem. Or you can create your own custom extractor.