Medallia (NASDAQ:MDLA) Shares Down 7.5%
Medallia (NASDAQ:MDLA)’s stock price fell 7.5% during trading on Thursday . The company traded as low as $26.26 and last traded at $26.26, 988,523 shares traded hands during mid-day trading. A decline of 0% from the average session volume of 989,387 shares. The stock had previously closed at $28.40.
A number of research firms recently commented on MDLA. Craig Hallum reiterated a “buy” rating and issued a $40.00 price target (down from $45.00) on shares of Medallia in a research note on Friday, September 6th. UBS Group began coverage on Medallia in a research note on Tuesday, August 13th. They issued an “outperform” rating and a $55.00 price target for the company. Stephens began coverage on Medallia in a research note on Monday, July 29th. They issued an “overweight” rating and a $52.00 price target for the company. Wells Fargo & Co began coverage on Medallia in a research note on Tuesday, August 13th. They issued an “outperform” rating and a $45.00 price target for the company. Finally, Credit Suisse Group began coverage on Medallia in a research note on Tuesday, August 13th. They issued a “neutral” rating and a $40.00 price target for the company. Two investment analysts have rated the stock with a hold rating and twelve have assigned a buy rating to the company’s stock. Medallia presently has an average rating of “Buy” and an average target price of $47.62.
The stock has a fifty day moving average price of $37.60.
In other Medallia news, Director Borge Hald sold 1,765,000 shares of the firm’s stock in a transaction dated Tuesday, July 23rd. The shares were sold at an average price of $19.53, for a total value of $34,470,450.00. The sale was disclosed in a legal filing with the SEC, which is available at this link.
About Medallia (NASDAQ:MDLA)
Medallia, Inc provides an enterprise Software-as-a-Service platform in North America, Europe, the Middle East, Africa, and internationally. The company's platform utilizes deep learning-based artificial intelligence technology to analyze structured and unstructured data from signal fields in human, digital, and Internet of Things interactions.
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