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Asset logo for symbol YEXT
Asset logo for symbol YEXT



AI Deep-Learning Forecast (YEXT)

Analyst Forecast

Period: Next 12 Months

Analyst Ratings

Yext (YEXT) Stocklytics Forecast

According to analysts, the stock price of Yext Inc (YEXT) is predicted to show positive growth in the coming years. The company operates in the digital knowledge management space and provides software solutions to businesses. With the increasing demand for accurate online information, Yext is well-positioned to benefit from this trend. Analysts expect the stock price of Yext to rise steadily over the next few years, reaching new highs in 2023. This forecast is based on the company's strong fundamentals and the industry's growth potential.

AI and machine learning technologies are also being utilized to predict the future price of Yext stock. These advanced methods analyze past data, market trends, and various factors influencing stock prices to make accurate predictions. The use of artificial intelligence in stock price prediction has gained significant popularity, as it can provide valuable insights to investors. AI-powered prediction models suggest that Yext Inc (YEXT) has the potential for substantial growth in the coming years, making it an attractive investment opportunity.

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Frequently Asked Questions

What is the analyst price prediction for Yext (YEXT) stock?

Analysts have set a target price of $11.57 for Yext (YEXT), based on forecasts from 14 analysts. The predicted price range extends from a high of $22 to a low of $5.25. This represents a potential increase of up to 308.16% and a decrease of -2.6% from the current price of $5.39. These forecasts are as of 2020 Mar 04.

What are the analyst ratings for Yext (YEXT) stock?

Currently, there are no analyst ratings available for Yext (YEXT), possibly due to insufficient coverage or recent updates.

What is the AI price prediction for Yext (YEXT) stock?

At present, there is no AI or machine-learning-based price prediction available for Yext (YEXT) stock. The lack of a forecast could stem from various factors, such as inadequate data or the necessity for model recalibration.


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