What is Google’s algorithm update history and how has it affected reputation management?

The named updates each addressed a specific class of manipulation and collectively pushed Google’s ranking toward signals that are harder to fake. Panda penalized thin content farms. Penguin penalized manipulative link building. Hummingbird shifted toward semantic understanding. BERT and MUM improved natural-language interpretation and reduced the value of keyword-stuffing. The helpful content updates explicitly target content written for search engines rather than users. And the AI integrations of the last two years have brought authority signals deeply into AI Overview generation. The practical effect for reputation work is that approaches that were briefly viable – link networks, content farms, keyword manipulation, low-quality syndication – now produce less and less return and increasing risk. The work that survives and compounds is the structural work: authoritative content, accurate entity signals, durable owned properties, source-level remediation. Programs built on that foundation get stronger with each update rather than weaker.