Social Media Actions Analytics
Actions Analytics is another type of “intermediate metric,” where the ultimate outcome of an activity in social media is unclear, but we still measure the engagement activity of users based on social sharing activities, etc. There are many platform tools, both free and paid, that help users measure social media actions, providing useful analytics (as long as they are not confused with ROI – return on investment) which action analytics are unable to provide.
Social media actions analytics deals with extraction, analysis, and interpretation of the insights contained in the actions performed by social media users.
Social media actions are of great value to social media marketers because of their role in:
- increasing revenue
- brand value, and
- loyalty.
Actions Analytics are not effective proxies for Return on Investment (ROI), and they are better suited to measuring the engagement that an audience has with the organization’s product or service.
Common Social Media Actions
- Like
- Dislike
- Share
- Visitors, visits, revisits
- View
- Clicks
- Tagging
Here you have an example on how to download and analyze social media data with Tableau:
A Few Actions Analytics Tools
- Hootsuite is an easy-to-use online platform that enables users to manage their social media presence across the most popular social networks. Hootsuite offers different plans depending on business needs and budget: free, pro, or enterprise.
- SocialMediaMineR is a social media analytics tool that takes one or multiple URLs and returns the information about the popularity and reach of the URL(s) on social media. The reports include the number of shares, likes, tweets, pins, and hits on Facebook, Twitter, Pinterest, StumbleUpon, LinkedIn, and Reddit6.
- Lithium (www.lithium.com/) is social media management tool that provides a variety of products and services, including social media analytics, marking, crowdsourcing, and social media marketing.
- Google Analytics (www.google.com/analytics/) is an analytical tool offered by Google to track and analyze website traffic. It can also be used to for blogs and wiki analytics.
- Facebook Insights (www.facebook.com/insights/) helps Facebook page-owners understand and analyze trends within user growth and demographics.
- Twitter Analytics
- Tweetreach helps measure the number of impressions and reach of hashtags. The tool can be accessed at https://tweetreach.com.
- Kred helps measure the influence of a Twitter account: www.kred.com.
- Hashtagify.me measures the influence of hashtags: http://hashtagify.me.
- Twtrland is a social intelligence research tool (http://twtrland.com/) for analyzing and visualizing our social footprints.
- Tweetstats: Using a Twitter username, Tweetstats graphs Twitter stats including tweets per hour, tweets per month, tweet timelines, and reply statistics (www.tweetstats.com).
Social Media Hyperlink Analytics
Hyperlink network analysis is important, as it is often used to understand or explain the spread of viral content and identify influential websites and webpages in a hyperlink network. Also, hyperlink networks are the foundation of off-page SEO and a vital part of the original Google PageRank algorithm. Hyperlinks are the pathways of social media traffic. Hyperlinks are references to Web resources (such as a website, document, and files) that users can access by clicking on it.
Types of Hyperlink Analytics
- Hyperlink environment analysis
- Co-link networks
- In-links and out-links networks
- Link impact analysis
- Social media hyperlink analysis
Network Analysis and Social Network Mapping
There are many types of networks and they can intermix, making social network analysis challenging and rewarding. The relationships of network nodes are more important than any other single factor in determining the influence and importance of that node in a network. The idea behind network analysis is the structure and interrelationships on a social network are as important as who is on the network, perhaps even more important.
This type of analysis vastly shortens the amount of time it takes to research prospective customers and industry influencers and provides valuable insights to gauge marketing effectiveness within the networks being examined. Some people on social media are more influential, from a marketing perspective, as they can share information with a large audience of followers, subscribers, and friends, and are considered opinion leaders. Social media Network Analytics deals with constructing, analyzing, and understanding social media networks. Networks are the building blocks of social media and can carry useful business insights.
Purpose of Network Analysis
- Understand overall network structure
- number of nodes
- number of links
- density
- clustering coefficient, and
- diameter.
Find influential nodes and their rankings
- degree
- betweeness, and
- closeness centralities.
Here is an excellent tutorial on social network analysis:
Mobile Analytics
There are three different type of mobile applications that could be used by marketers (mobile, Web, and hybrid) and the pros and cons of each one. The majority of online activities now happens on mobile devices and website owners should make sure their websites function well on mobile devices for a variety of reasons, including ecommerce and website search engine rankings.
Mobile Analytics is used to analyze the activity of device users. Unfortunately, many mobile analytics platforms are based on or a derivative of Web Analytics platforms, this pedigree limits their usefulness as the technology behind mobile devices is much different than the rest of the Web, and Web Analytics visualization are not always well suited for mobile device readouts. As a consequence, specialized mobile analytics platform evolved, competing with Web Analytics platform that claim to perform the same services. Soft assessments from Demand Metric can be used by stakeholders to decide what kind of application to develop, or what level of mobile marketing they can sustain.
Aligning Digital Media with Business Strategy
A marketing analytics strategy focuses on planning a data-driven project to maximize marketing effectiveness, evaluate marketing performance and find ways to improve the effectiveness of marketing measures. This type of analytics strategy helps maximize efficiency and minimize marketing costs by accurately reporting on the past, analyzing the present, and predicting the future.
In the marketing campaign life cycle marketing analytics can help through all the stages, including the design, by starting with exploratory research, customer listening and social media analytics, A/B tests in the implementation tests, then constant monitoring and evaluation of the campaign to compare results to original goals and assess how to improve outcomes.
The first stage in the marketing analytics strategy is to identify the metrics to be used, in which marketers need to be clear regarding their objectives, use metrics to provide answers to issues and track the status of a marketing process, as well as to determine if goals are being achieved.
The second phase requires marketers to analyze the metrics. Businesses need to have systems to track the important metrics, which usually include Web Analytics and Marketing Automation Dashboards. In this stage, marketers can use the new information to compare the current state to benchmarks, such as historical Trends, Industry Average Performance, and competitor performance. After analyzing performance, the reasons for increased or decreased effectiveness need to be assessed.
The last phase refers to strategy improvement in order to increase efficiency and develop solutions to problems through different tools, including A/B testing and experimenting. This phase represents an outcome of using marketing analytics metrics, as their purpose is to help with analyzing data and extracting useful intelligence to improve business effectiveness.
How can companies like Three Squirrels use business analytics to improve their competitive advantage and find a market niche? What kind of analytics should your employer or your company use more?
Business analytics can help companies to personalize their offer.
For segmentation and targeting, the analytics tools can result in a more precise and relevant result which include the context and information about the consumer purchasing behavior in addition to socio-demographic criteria. For instance, companies will not only target an ethnicity or an age, but they will cross these indications with the geo-location, the weather, channel usage… Analytics provides a better customer profiling.
In addition, for Customer Life-Time Value, companies could use a technology called supervised learning. This program is a useful tool to invest on the most profitable customers. And it’s possible thanks to the analysis of data such as the channel through which the customer entered in contact for instance.
Analytics is also at the base of Recommendation Engines. For example, when a customer goes on Amazon, they can see a collaborative filtering regarding what they want to purchase. If they choose to buy a phone, they will see that other people who have bought this item have also bought other items like a phone case. Another example is the content-based filtering. If a customer watches a fantasy movie on Netflix, the platform will recommend other movies with the same topic. So, the technology is capable to process a large amount of data, trying to have a better understanding of the customers, to increase the cross sells and the average order value
So companies should focus more on prescriptive analytics to adapt the strategy (outcomes) to the different customers desires and consumption’s behavior.
Business analytics is the process of collecting, sorting, processing, and researching business data, as well as using statistical models and interactive methods to transform data into business insights. The purpose of business analysis is to determine which data sets are useful and how they can be used to solve problems and increase efficiency, productivity and revenue. Here are some ways that E-commerce companies like Three Squirrel to improve their competitive advantage:
– E-commerce data helps companies with management, inventory, supply chains, forecasting needs, better pricing strategies and sales strategies. Another benefit of e-commerce is the flexibility to define the best way to streamline tasks across different channels.
– Customers always want to take quick action like I want to go, I want to buy and they access their smart phone. Smartphone technologies can help companies to use these moments in order to study the nature and action patterns of the consumer.
First-of-all, since the company is targeting mostly the millennials and young women, it should be focusing on the social media analytics to determine better their activities and the trends to follow. Companies like Three Squirrels could use business analytics to improve their competitive advantage and find a market niche thanks to data mining and predictive analytics to be able to collect data and tailor the products to the consumers’ willings and in order to forecast future results. Predictive analytics could be very useful in the sense that the company is looking towards innovation so based on the trend data collected some assumptions will be done to make projections. Hence, three Squirrels will be more competitive thanks to some forecasts in sales and marketing for example. The kind of analytics which should be more used in alignment with this strategy are the leverages of search engine optimization like Google Analytics/ Web Analytics which can measure the effectiveness of viral marketing. What could be a very good option for that kind of brand would be to have some influencers to promote Three Squirrels on social medias to the young generation and use some analytics like Traackr to do so. Concerning the analytics for social media they are diverse (ex: Geo-data for Instagram).
Nowadays the majority of people spend a significant part of their daily lives online and this is the reason why an enormous quantity of data is created. The analysis of the available data is incredibly precious for companies that can have a direct contact and insights about their customers’ behaviour. Furthermore, business analytics allow companies to better perform as they have more precise information about their consumers, their supply chain, their value chain, etc.
Among the most important things that analytics facilitate there is marketing, in particular the process of segmentation, positioning, targeting, differentiation and loyalty that makes it easier for organisations to find their specific niche. For this purpose analytics are very important, such as the demographic ones that help to better understand the needs of the consumers, the geo ones and industry trends that facilitate the decision of where to develop and expand the business, the supply chain analytics that help a business to better predict future demand and to have a more efficient and fast supply chain.
The online marketing space is in constant shifts as new technologies, services, and marketing tactics gain popularity and become the new standard. Online store owners are one of the many different segments affected by these constant evolutions. In order for these business owners to survive and thrive, they need to be able to make better decisions faster. Thus, companies like Three Squirrels could use analytics to better understand the behavior and functioning of their target customers. Moreover, it is important for them to understand what is working and what isn’t, in order to focus on the most profitable channels. Lastly, having access to statistical information from all areas of their online marketing and sales activities would give them an advantage over competitors that do not have this information.
Two types of data would be relevant: predictive analytics to try to forecast the trends and the future events; and prescriptive analytics to try to improve the future outcomes. The company should also rely on web, social media and mobile analytics.
The online marketing space is in constant shifts as new technologies, services, and marketing tactics gain popularity and become the new standard. Online store owners are one of the many different segments affected by these constant evolutions. In order for these business owners to survive and thrive, they need to be able to make better decisions faster. Thus, companies like Three Squirrels could use analytics to better understand the behavior and functioning of their target customers. Moreover, it is important for them to understand what is working and what isn’t, in order to focus on the most profitable channels. Lastly, having access to statistical information from all areas of their online marketing and sales activities would give them an advantage over competitors that do not have this information.
Good points regarding the importance of constantly monitoring marketing activity and adapting based on analytics.
As the other said analytics is really important and essential nowadays. Indeed, it makes it possible to gain in competitiveness because it quite simply makes it possible to have information on consumers or to know their intention of purchase or to know what they think of our brands or our company. The Data collected and analysed will make it possible to make relevant recommendations, to help them in their research or to create a product or service adapted to their request.
In this age of the internet and google it is crucial for a company to have analytical tools. However, not all companies can afford everything. This is why this video ( A.I. for Marketing & Growth – Where do I start? https://www.youtube.com/watch?v=Ra_yTQnhf_8 ) explains the order of priority of the tools to have for a company in order to gain in performance and competitiveness.In the video we see 3 categories:
• The mus have for the companies: Predictive analytic + Clustering and customization.
• The should have for the companies: The recommendation engines + The natural language processing (NLP)
• The nice to have for the companies: Psychographics personas + Image recognition
– Predictive analytic: they can predict futures outcome based on historical data. It is easy to implement and to prove. It helps marketers to understand the futures needs, the futures way of life, the futures loyalty behaviors of the customers. It is a form of supervising learning.
– Clustering and customization: It is a form of unsupervising learning, that is mean it is when you do not know what you are looking for. The learning machine algorithm will throwing of many data at the problem and will solve the pattern for you. Solving the patterns permit to the marketers to make a segmentation of the customers. (Age, gender, income, device…). It is call the data-driven segmentation.
– The recommendation engines: Use in order to find some recommandation for the customer. The most famous example of recommendations engines are Netflix or Amazon recommendation.
– NLP: it consist to asking to the computers to understand and reproduce human language. It is used for sentimental analysis. It shows what customer think about us, about our product, our brand, our competitors.
– Psychographics personas: It is mix demographic segmentation and behavior segmentation. It can show a mix of the personality, the interests, attitude, and behavior of the customer.
– Image recognition: It is simply about face recognition for example. However, it is a new concept, which are not really use today; it will be the future of marketing analytics.
Excellent points, I completely agree with you, excellent overview of analytics