GOALS & OBJECTIVES

Part 2

·       Applicable (or appropriate) – a company should determine whether the campaign that they decided to run is applicable in achieving their goals. 

·      Realistic (or relevant) – companies should make sure that the objectives they are trying to set are realistic in achieving their goals. Can we achieve our goal with the campaign that we picked and with our available resources?

·       Time-oriented – should determine the time when the results can be achieved. Setting a specific time frame will help companies to plan and evaluate their campaign.

 

Tracy L. Tuten provides a good example of SMART social media campaign objectives in her “Social Media Marketing” book¹, the first example illustrates the wrong way of planning campaign objectives and second example illustrates SMART objectives: 

1.     “We will tell everyone we can about our new Facebook page and see if they like it so much they’ll buy more of our product.”

2.     “We will promote our new Facebook page in print advertisements we will place in the June issues of Rolling Stone, Sports Illustrated, and Maxim. On July 15 we will count the number of Facebook users who ‘like’ our brand and compare sales to the same period previous year.”

Sources: 1. Tracy L. Tuten "Social Media Marketing" 2 edition, page. 298.

GOALS & OBJECTIVES

Part 1

In order for a business to track campaign performance or website performance it is important to set specific goals that the company is trying to achieve. Every company sets different objectives that will help to accomplish their goals. Some companies may choose to run a campaign with the goal to improve SEO ranking for their website so it would show up on the first page of an organic search. Others may choose a goal to increase sales. They may choose to write a blog about their business in order to educate people about products or services that they offer and incentivize readers to make purchases. It is important to set SMART (specific, measurable, applicable, realistic, time-oriented) objectives in order to achieve certain goals. How do we know if our objectives are SMART? By following these steps:

·      Specific – when running a campaign or writing a blog, companies should determine what they are trying to achieve from these activities. For example, if a tour company wants to increase sales by running an ad campaign they should be specific about the desirable outcome, such as “increasing the number of summer tour sales by 20%” compared to previous summer sales. They should also specify the time in which they will strive to get desirable results. 

·       Measurable – how is the company going to measure the success of a campaign? Numeric or descriptive measurements should be considered and applied to measure the success of an ad, blog page, campaign or website performance. What can we measure? E-commerce websites can measure percent of the sales increase, blog pages can measure the amount of viewers on the page and links to their page, social media campaigns can measure ‘likes’, ‘shares, ‘engagement rate’, and ‘traffic to companies websites.’

Data Monetization

“Data is power.  It differentiates and becomes the basis for new products, sales and customer relationships.   A company’s ‘optimal exploitation of data’ is key, but more importantly, that exploitation drives revenue.”

Josh Siegel

By collecting and analyzing a vast amount of customer data companies can better understand their customers’ needs and offer products and services to satisfy those needs profitably. It is important for the marketing department to coordinate with the information technology department to ensure a sufficient amount of data is being captured and utilized in the most efficient manner. By working together, the two departments can adjust their techniques as they learn about customers changing behaviors towards a certain product or service.

Some examples in which businesses can monetize their data include:

·      Grocery stores can offer customer loyalty cards that incentivize customers to shop with their cards. By collecting data through the use of the loyalty card, companies gain insights about customers buying patterns (such as what they are buying and where) and preferences and can use that information to smartly send relevant offers with a higher degree likely success.  Also, by monitoring customer buying patterns, grocery store management can send personalized offers of correlated products to their clients and adjust inventory based on their data.  

·      Companies in the hospitality industry own enormous amount of data about their customers (from collecting information they acquire when customers book hotel rooms or through other customer serves) and use that data to improve their client’s satisfaction rates and gain customer loyalty. For example, by utilizing analytics tools and performing sentiment analysis, hotels gain insights about customer reviews concerning their hotel on a variety of social media channels and learn about their clientele’s level of satisfaction from staying at their hotels or from using their services. After analyzing customer reviews and understanding what customers like and dislike, they can build recommendation systems or run targeted marketing campaigns to improve their customer satisfaction rates. Also, by having insights about customers booking history, hotels can create personalized offers for their clientele. For example, by collecting information from room service orders, hotels can adjust restaurant menus, learn about client’s allergies and provide an outstanding level of personalization.  

·      Transportation industries are also using data to leverage their business performance. Uber is a great example in which utilizing customer data changed the way an established industry operates now. Their branded app enables customers to order a car and allows them to receive important information such as estimated arrival time, travel duration and total cost of the ride. This unique information and data-driven service resulted in Uber gaining an enormous amount of customers. By effectively using data, Uber can determine where to situate their cars to minimize customer pick up times and maximize driver profitability. They also analyze their data to determine what complimentary businesses they could enter into such as food and package delivery services. By tracking driver’s locations at all times, the company provides a higher level of perceived security to their customers. When receiving complaints concerning unsatisfied rides, the company can check the data about that ride and monitor their driver’s performance- such as route and speed to make decisions about how to solve the problem in order to improve customer service, gain customer trust and loyalty- all in order to gain a larger market share and leverage their business.  

There are different ways in which companies can acquire data about their current or potential customers, some of them are: collecting information about customers and their reviews through social media channels, acquiring information through company transactions, conducting customer surveys and many more.  There is tremendous potential for companies that know their goals and know how to collect, analyze and utilize the data. Data can bring big value to a company, help to make better business decisions and leverage business performance.

Data Visualization

“By visualizing information, we turn it into a landscape that you can explore with your eyes, a sort of information map. And when you are lost in information, an information map is kind of useful”

David McCandless

 “Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns (SAS).”

Interpreting large amounts of data can be a long and challenging process and with the evolution of the variety of data visualization tools businesses can interpret data much faster and easier. The way in which a human brain works is that it’s much easier for us to look at pictures and graphs and understand a variety of changing patterns in a data set, than looking at a large table with enormous amounts of number sets and trying to compare those numbers, interpret them and make the right business decisions. The goal of data visualization is to enable people to read and interpret a variety of correlations, patterns and trends much easier and faster by being able to see the data in a visual context.

Some of the most popular data visualization tools are:

 Tableau Software – one of the most popular software programs that enables people to see and understand their data and help business representatives to make faster and better decisions. It enables users to get fast insights about particular data sets, create presentations and share them easily with colleagues. Everyone can use this software- it’s offered in different versions including desktop and cloud versions.

   SAS Visual Analytics – it offers a plethora of reports that illustrate how visual analytics can be applied to questions and problems in a variety of industries. By utilizing a variety of visual graphs it enables business representatives to see the bigger picture and underlying connections.

  Qlik – allows you to create dashboards, visualizations and apps that helps company’s answer most important questions. 

  Microsoft Power BI – allows analyzing and visualizing data in order to make better business decisions.

 Oracle Visual Analyzer – a web-based tool that enables users to explore analytics data visually and on an individual basis. 

  Plotly, DataHero, Chart.js and many others.

There are a variety of charts and graphs that can be utilized to visualize and interpret data sets; some of them are:

•  Line Charts- illustrate the relationship between one variable to another and are commonly used to track trends over time. They can be utilized for tracking multiple data sets on the same chart to visualize correlations and trends.   

• Bar Charts – mostly used to compare the quantities of different categories of groups. Bars represent a category of a certain value. In order to provide visual variance we can utilize a variety of colors for a bar category (see picture below).  

• Scatter Plots – a two-dimensional plot chart that illustrates the joint variation of two data items (see an example below). They can be utilized for analyzing the relationship between different variables. They can be also utilized for applying statistical analysis with correlation and regression.

           

• Bubble Plots – a type of a scatter plot in which the dots or squares are replaced with bubbles and numerical value visualizations in the scale of its circular bubbles. It enables users to illustrate the relationship among at least three data series. They can be utilized to interpret medical, economical, and other scientific relationships.

  

  Pie and Donut Charts – utilized to compare the parts of a whole.

Pie Chart

                          Donut Chart

                                                       

   

•       Heat maps – illustrate the data in which values are represented by colors. There are a variety of colors that can be utilized to illustrate the heat map. One on the most recognizable way of utilizing a heat map is the presidential election. A geographic heat map is marked with two colors (blue represents a democrat candidate and red represents a republican candidate) and therefore the heat map illustrates which states or regions each candidate has won. 

               Find more information about Data Visualization on Kayli Tarcy's blog.