Across our marketing articles you'll find a range of guides, strategy tips and analysis from some of the biggest names in SEO to build your knowledge and create winning campaigns.
Dom O‘Neill breaks down how you can use nanocasting to help your business grow its products and services. Learn the proper way to send private video messages to those that already like you, trust you, and who already buy from you. See Dom‘s strategies for saying the right things at the right time without spamming to create a conversation.
We had a fantastic Twitter chat with John Doherty about hiring the right marketer for your company. Our community discussed the types of skills marketers need today to build their reputation, ways a business can vet remote workers and consultants, why a company would choose a consultant over an agency, determining which level of marketer to hire, and which questions you should ask when hiring.
During pride month, brands teeter between a genuine celebration of Pride and problematic advertising that feels forced, or worse: pandering. Keep reading to learn what makes brands come across and fake, and what brands should be considering (and avoiding) before they attempt to include Pride as a part of a marketing campaign.
Our last #SEMrushChat discussed “How to Hack Your Competitors’ Marketing Strategies“ with guest Joe Youngblood. The responses from our community showed that gathering data from your competitors is not as simple as most people believe. With experience comes knowledge, and our community offered their expertise. Keep reading to view their insights, which should help you when evaluating competitors.
Want to see examples of successfully implemented tone of voice illustrated by brands’ 404 pages? Dive in to learn how to find and implement a tone of voice for your brand in five steps. You will also discover why it is crucial for any business to have a consistent tone of voice and who has the expertise to define it.
Textual data are everywhere; social media posts, keywords, URLs, page titles and more. They also come with a lot of numbers that describe them. How we can extract meaning from text data on a large scale? What techniques can we use to quickly figure out important topics, users, or maybe products, in a set of textual data?This is a tutorial that uses data science techniques to solve these questions.