Ziff Davis B2B

Posting authentic online content from your brand or employees has proven to be an effective customer engagement and marketing strategy. Further, there is a wealth of data to show you how to reach customers with personable content.

Brand awareness is the degree to which a customer is able to recall and recognize your brand. Brand awareness is critical for promotion and marketing, especially for a young company. High brand awareness can result in a company becoming very popular or “trending.”

Case management is the optimization of customer care through the construction of a network of formal and informal activities, services, and supports. 

Companies post content to their websites, newsletters, and social media accounts based on social media metrics that indicate when posts receive the most engagement. This engagement varies by social media site, industry, content type (promotion, article, etc.), and the time of posting: post engagement varies by weekday and even time of day. A content calendar, then, is the scheduling of content publication to increase engagement and conversion.

Companies also schedule site maintenance on these calendars, to ensure they only occur during times of least engagement.

Other terms for content calendar include editorial calendar, social media posting schedule, and other variations of these. An editorial calendar, however, focuses on content planned for company-managed websites plus social media accounts. Social media content schedules, on the other hand, focus on social media posts, as the name indicates.

Content, whether in the form of a video, a newsletter, an ad, or anything else, needs to reach the target audience at the right time to make an impression. A good content distribution strategy, then, finds the best ways to provide content to audiences.

Content distribution involves using at least one of a number of distribution channels: paid, owned, or earned. Paid distribution channels include advertisements; owned channels include company newsletters or websites; earned channels include shares and reviews.

Customer lifetime value (CLTV) is the expected profit that a single customer brings to a company over the course of their lifetime. CLTV represents a shift in emphasis from quarterly or annual profits to the long-term relationships with customers.

Everyone wants more leads, but the more we are able to generate, the harder it becomes to identify which of them are actually worth the time and effort spent in order to try to convert them. Lead scoring models let you automatically rank your leads in order of the perceived value each lead represents to your company. Resources for marketing and sales can then be distributed by the priority determined by lead scoring.

Sales forecasting is the system by which future sales volumes are estimated—at what price, during which time, and in which market. Product performance forecasting enables businesses to make informed decisions in both the short term and the long term. Machine learning software is continually improved, providing businesses with better analysis all the time—faster and more reliably than manual methods.

The abundance of job seekers nowadays leads many companies to use machine learning throughout their recruitment process. Some examples of this can be found in the fields of talent management, talent attraction, and candidate selection.

Talent management entails understanding the best fields, positions, and backgrounds to set talent up for success. Talent attraction selects the top outlets and channels for attracting the most suitable employees. Finally, candidate selection use neuro-linguistic programming (NLP) tools on CV’s to find suitable candidates.

Remarketing campaigns show ads to people who have visited a business’s website or downloaded one of its apps. Remarketing is designed to get potential customers who have shown interest in your product or service to recall your business and their intent to buy, therefore enlarging the odds of them converting.

AI has been used to improve supply chain and demand forecasting for a couple of decades. Demand planning applications use data driven algorithms to take historical data and use it to forecast. Demand forecasting can include promotion planning or stock and sales forecasting. The machine looks at the forecast, compares it to actual shipments, and suggests alternatives and optimization options. Over time, many companies started doing more specific forecasting for specific regions, products or stores or for more granular points in time. Both retailers and their suppliers (CPG companies or 3rd party shipping and supply chain companies) use their data to help conduct automated decision making within the supply chain.