Natural Language Processing (NLP), or the AI-driven means by which computers can understand our human language when interacting with them, is something every one of us will have now been exposed to in the Western world. Whether it’s ordering a pizza through your Google Home device or asking Siri if it’s going to rain, the chances are that you’re already using NLP in your daily life.
But how will this newly mature technology affect us as marketers? Can Natural Language Querying (NLQ) via NLP (in the form of conversational analytics, i.e. the ability to ‘talk to your data’ or ‘type questions directly to your data’, rather than the perhaps more widely-recognised text analytics capability) help your company to better interrogate your data across a much broader set of issues than you’re currently able to tackle? And how can querying or talking to data be successfully integrated as a practice to deliver promised benefits for your brand?
In this paper you’ll discover:
- Some context around this revolution in Business Intelligence (BI)
- The barriers to NLQ’s successful implementation
- How some of these issues may be overcome
