Artificial Intelligence And Social Media. How AI Can Improve Your Job Not Steal It.

Artificial intelligence (AI) is a buzz word that can be confusing and even scary. Some predict AI robots will replace humans, but in this article I will focus on what AI exists now and how it is helping or could be helping your social media strategy. AI empowered social media can assist in many areas such as content generation and optimization, 24/7 engagement, automated bidding and placement of social ads, enhanced audience targeting, automated analytics, personalization, and social listening.

AI and Big Data

Artificial intelligence is simply computer systems performing tasks that normally require human intelligence. In the world of big data AI comes in handy. Big data is the massive amounts of data so large and complex it can’t be processed with traditional data applications. This consists of structured data organized in databases and spreadsheets and unstructured data in free-form text, images and video in documents, articles and social media. IBM reports 2.5 quintillion bytes of data are created per day and over 80% is unstructured with much of that from social media.

Algorithms

An algorithm is a series of steps performed by a set of rules to perform a function. We’re most familiar with algorithms as the rules that decide what appears in social media feeds. We try to determine social network algorithm signals to increase our organic reach. Alternatives include paying for social ad placement or influencer marketing. AI can improve social ad campaigns and improve influencer marketing. AI in influencer marketing can aid in finding and vetting ideal micro-influencers for brands.

Automation

Automation is software that does things without human intervention. Examples include Amazon tracking shopping history to suggest similar items to automate cross selling. Automated testing pulls data to generate scheduled reports. Automated reminders help employees and customers through alerts and notifications. Drip marketing automates sending a series of communications on a schedule or by consumer trigger actions. Drip marketing has used email for years but also now uses chatbots in Facebook messenger.

Machine Learning

Machine Learning is when computers learn from experience by modifying processes from new input. Machine learning can use algorithms to try random variables learning which work best to achieve a goal such as lowest cost per impression or acquisition. Programmatic advertising uses machine learning and automated bidding and placement for media buying. Deep Learning goes further with data processing on a neural network for faster more complex learning. Pattern recognition is a form of machine learning where a computer can be trained to detect patterns in text or visual data.

Natural Language Processing And Generation

Natural language processing (NLP) finds linguistic patterns to analyze and synthesize speech. This is how Hootsuite Insights determines sentiment of brand social media conversations. It can also help with crisis management. Dataminr uses NLP to monitor real time social conversations for crisis communication and real time marketing. Natural language generation (NLG) takes non-language inputs and generates spoken language. Phrasee uses NLG for AI-powered copywriting creating data-driven, human-sounding brand copy for Facebook and Instagram.

Image Recognition

Image recognition or computer vision is software that can recognize people, animals and other objects. Brandwatch has an image detection and analysis tool that finds images containing a brand to report how, when, and where consumers are seeing it. CrowdRiff uses image recognition to discover user generated images (UGC). They combine this with brand owned images and performance data for content optimization. Pinterest has AI powered visual search called Pinterest Lens. Marketers can purchase search ads to appear in that search and use Shop the Look pins.

Predictive and Prescriptive Analytics

Predictive Analytics helps understand future performance based on current and historical data. Prescriptive analytics helps determine the best solution among various choices. Salesforce’s Einstein uses AI for customer and lead predictions and recommendations. Einstein analyzes sentiment and intent to route social conversations to the right person streamlining workflow. IBM’s Watson uses AI for campaign automation and marketing personalization. Virtual Assistants add human interface to software. Watson Assistant replaces tedious queries and spreadsheets with simple questions such as, “How did social media perform this month?”

Chatbots

Chatbots use AI to simulate human conversation through voice commands or text chats. Chatbots can be used for drip marketing automation, lead nurturing, onboarding, renewals, confirmations, and engagement. AI-empowered chatbots can also help lead customers through the sales funnel (AIDA). For awareness bots can initiate conversation at scale communicating one-to-one with 5 or 500 people. At the interest stage bots provide 24/7 engagement at the moment of interest. In the decision stage bots supply information, answer questions and send content. For the action stage smaller purchases can be completed by the bot or hand off more complex ones to a human.

Social Care

AI-powered support can improve customer service via social media. ManyChat’s Facebook Messenger chatbots give customers convenience and speed. Simple chatbots spot keywords and respond with predetermined answers. AI-powered chatbots use NLP to create conversations like human agents. When problems get too complex chatbots can recognize this and hand off the conversation to a real agent. Some report chatbots could save businesses $11 billion in support costs by 2025.

Social Ad Optimization

Pattern89 uses AI to analyze billions of data points daily to discover what social ad dimensions drive customer behavior. Their AI analyzes every combination of placement, device, interests, age ranges, behaviors, demographics for custom optimization insights. Clinch provides personalized programmatic social media content across the customer journey. AI enables them to generate unlimited personalized ad versions with real-time optimization for text, image and video. Motiva AI works with Oracle’s Elogua marketing platform to scan campaigns and make performance recommendations, optimize time and frequency suggestions, run auto multivariate messaging experiments, and automatically discover new audience segments.

Privacy And Ethics

With the General Data Privacy Regulations (GDPR) in Europe and new U.S. regulations like the California Consumer Privacy Act (CCPA) marketers are concerned about compliance. Charles Taylor argues that AI could help with consumer privacy protection. For example, Anyclip AI identifies video events and actions for contextualized social media ad placement. Using this AI could allow custom targeted messages without accessing third party consumer data. AI could also improve targeting to insure ads don’t appear with objectionable content. AI can also help with issues like cyberbullying. Instagram is using AI to identify negative comments before they’re published asking users, “Are you sure you want to post this?”

For the social media professional AI can help improve your job.

Gartner describes AI as a way to automate manual time-consuming processes to free up time, so marketers can be more strategic and creative. Pattern89 sums up the advantages of AI saying “AI algorithms work quickly and thoroughly, and they understand more data than a human can analyze within a single lifetime.” According to Adobe, the top marketing uses of AI include analysis of data, personalization, optimization and testing, image recognition, automated campaigns, content creation, programmatic advertising, digital asset management, video recognition, creative work, and automated offers. How are you using AI to improve your social media performance?

A Simple Guide to Influencer Marketing in Social Media.

Influencer marketing is a growing part of social media strategy. According to the Association of National Advertisers (ANA) 75% of companies have influencer programs and nearly half (43%) are planning to increase their spending next year. Of companies not using it over a quarter (27%) plan to do so. Yet, there are many forms and methods to structuring an influencer program. To be successful brands must ensure they have a solid strategy rooted in business objectives, target market and best practices. Below is a guide to follow in creating or optimizing an influencer marketing program as part of a broader social media strategy.

Guide to Influencer MarketingObjectives and Target Audience: Begin your influencer marketing with business objectives. Are you trying to increase sales or build brand awareness? Do you have a reputation problem and are looking to increase positive sentiment? Are you a B2B brand that wants more leads? Look for the bigger problem or opportunity. Don’t make the mistake of starting with social media objectives that just become an end unto themselves.

Who are you trying to reach? Identify the target market for your product and service. Then turn that market into a target audience or audiences that you want the influencers to reach. You may have one audience active on specific social media platforms. Knowing this will focus your effort on finding influencers popular on those social channels. If multiple target audiences are involved identify every target by objective. Each audience may need to be reached with different platforms, influencers and content. An example is colleges with an annual enrollment objective targeting high school students, parents and alumni. They may also have a second objective of raising funds for a building project targeting alumni, business leaders and state legislators.

Method and Compensation: Influencer marketing can be structured in several ways. Small organizations with a minimal number of influencers or big companies with larger internal resources may want to create and manage their own influencer program. For more help brands can work with influencer platforms or networks that streamline processes and payments and make it easier to find influencers. Fees are charged for the convenience and you may be limited only to influencers in their network. A third option is hiring an Influencer Agency. These agencies provide the most options, customization and access to influencers, but will also cost the most in fees.

Another increasingly popular option for influencer marketing is affiliate programs. Affiliate marketing has been around for many years, but in the past it focused on building websites to draw an audience and send traffic to product links for sales. The retailer rewards the affiliate for each visitor or customer. Today more affiliates are using social media to attract audiences and insert links in social media posts. Instead of paying per post or sending free product, brands pay a commission per sale which could motivate affiliates to send traffic for a longer periods. Options include building and managing a brand affiliate program, working with an affiliate platform and network, or hiring an affiliate agency.

Social Channels: Select the social platforms that make the most sense for brand objectives and target audience. Where is the target audience spending time? What social media networks are they on and where do they look for content in the brand’s industry? Consider options in multiple categories such as Instagram, Twitter, Facebook, Snapchat, LinkedIn, YouTube, blogs, and podcasts. Also look at niche social platforms such as forums, Medium, Reddit, Quora, or SlideShare. The idea is to match social channel users and social channel content type with target audience and objective.

Type of Influencer: Are you looking for a celebrity (famous in traditional media), a social media star (known for or because of social media ), or a thought leader (known for industry knowledge)? Celebrities can have a lot of advantages including their mass reach and appeal. Yet film, music or sports celebrities can be expensive and people may question the authenticity of their product endorsements. Social media stars may have less followers, but those followers could be more engaged and endorsements could be seen as more believable. Thought leaders are a good choice for certain product or service categories in B2B. A mention or recommendation by an industry leader can carry a lot of weight.

Influencers can also be categorize in terms of follower size. Macro-influencers have 100,000 or more followers. Mid-level-influencers have between 25,000 and 100,000 followers. Micro-influencers can have as little as 50 to 25,000 followers. It may be tempting to only go for the macro-influencers because of their massive reach, but micro-influencers are often more effective. Adweek reports micro-influencer engagement rates can be 60% higher, their buys are 6.7 times more efficient, and they can drive 22 times more conversions. According to the ANA more than half of brands use mid-level (66%) or micro-influencers (59%) while less than half are using macro-influencers (44%). No matter what type of influencer you use a growing concern is influencer fraud. Influencer marketing software companies are working on ways to detect fraud and create industry standards.

Type of Content: Once you have your influencers decide how content will be created and spread. You may think it is best to have the most control, but content created by the brand and merely shared could come across as not genuine. Certain influencers or influencer networks may also have their own standards for what they will or will not do. Consider the pros and cons for each option such as influencer shared brand content, influencer created brand content, or product and service reviews and mentions. Or get creative with options such as influencer brand account takeovers, brand guest content contributions, or collaboration on a contest or giveaway. Another consideration is to repurpose influencer content in other channels and in other forms.

Monitoring and Metrics: Ensure you follow the FTC Endorsement Guidelines. Recently the FTC cracked down by sending out letters to influencers and brands not following the standards and creating deceptive advertising. Brands are responsible for training influencers on these standards and for monitoring their influencers to ensure compliance. Influencers, agencies and brands are all held accountable. Also make sure you have an up-to-date social media, user generated content, and privacy policy. After the Cambridge Analytica scandal and the new European data-protection law (GDPR) many companies are updating their privacy policies to meet new expectations and standards.

Finally, monitor key metrics per influencer and social channel to measure success. Be sure to identify KPIs that connect back to each business objective. This not only helps prove success but also allows you to optimize the program over time by social channel, influencer and type of content. Setting up key metrics and monitoring in the beginning will simplify social media metrics and help prove ROI. Not all marketers are effectively measuring influencer marketing, but according to the latest State of Influencer Marketing Report, 70% are measuring ROI and those firms average an earn media value of $5.20 per dollar spent on influencer marketing.

As other forms of traditional, digital and social media marketing become more challenging many marketers are adding influencer marketing to their IMC mix. Consider these guidelines when structuring or restructuring your influencer efforts.