Social Media Spending Reaches Record Highs. Ask These Questions To Ensure You have The Right Strategy.

The Covid-19 pandemic has lead to businesses shutting down, declining revenue and economic recession. Many in the social media marketing field have been uncertain about how this would impact budgets. But according to the latest CMO Survey spending on social media marketing has grown to record levels with a 75% spike since February 2020.

How Covid-19 Influenced the Importance of Marketing in Companies
The CMO Survey (https://cmosurvey.org/)

Social media spending reaches highs predicted for years.

The percent of marketing budget spent on social media has hovered around 10%-13% since 2014 while marketers always predicted it would reach 20% or higher. With the pandemic spending has finally reached 23% and marketers expect it to stay that high for the next year. The CMO Survey reports this in the context of declining overall budgets and revenue, but as those declined the average percent of revenue spent on marketing increased as most perceived it to be more important during the pandemic.

Why such a sudden and dramatic jump?

Part of this jump is certainly people using social media more. After years of stalled gains eMarketer updated predictions indicating US adults will spend 7 more minutes per day on social networks in 2020 than in 2019. But according to the CMO Survey marketers have also become more confident in social media’s contribution to company performance. After remaining flat for years marketer confidence in social media performance increased 23% from February 2020.

How was social media used during the pandemic?

The CMO Survey reports marketers used social media the most for:

  • Brand awareness and brand building 84%
  • Retaining current customers 54%
  • Acquiring new customers 51%
  • Brand promotions 48%

What does this mean for your social media strategy?

As marketers reduce spending on traditional advertising, they are shifting resources to digital and social. With this increased spending comes higher expectations. Now is a good time to check your social strategy to ensure you are headed in the right direction. Make sure your social media is focused on the right objectives, on the right people, with the right message, and in the right places.

Do you have the right objectives?

Are your objectives focused on building business like the one’s above? Or are your objectives focused on building social media vanity metrics such as followers, likes, comments and shares which make social media an end unto itself? Ensure that your objectives connect to company performance not social media performance.

Are you reaching the right people?

Have you identified a target audience based on a well-defined target market for your product or service? Or are you casting a wide net hoping to catching anyone who could use the product or anyone on the social platform? Look at customer data to determine who actually buys your product not just follows your social account.

Are you posting the right message?

Are you creating unique messages that speak to a well-defined audience with content customize to the social network? Or are messages more generic and content the same across social channels? Optimize content to increase performance.

Is your brand in the right places?

Are you on social media channels because you have been on them for years or because they are popular? Or have you evaluated social channels based on user demographics and engagement metrics of where your focused audience is most active? Take time to evaluate brand social platforms for wasted effort and missed opportunities.

Social media marketing has reached record highs and looks like it will remain there for at least the next year. As spending increases make sure your social media strategy will be as effective as possible.

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?