Dataset is in WASM cannot be put into a shared folder and will need to be created in a user account.
In the personal folders of email@example.com accounts, we have put the Telco WASM project.
One of the most common uses of Watson Analytics for Social Media is brand analysis. This blog will walk you through six considerations when producing analysis on a brand using social media data. The blog is complemented by this short video. The goal here is that you will get an idea of how you would go about doing a brand analysis on a Telecom company after reviewing these considerations.
1. Getting your data right
When starting an analysis on a brand, ask yourself the question, can the brand be confused with something else? For example, while Sprint is a company providing Telco services, it could be referenced in a running race. Perhaps the brand is so pervasive such that it is referenced in ways that are outside the scope of your analysis. Consider the AT&T Center, the multi-purpose sporting arena; people referencing the AT&T Center may be referencing a sport rather than the actual brand.
The most typical situation which presents a challenge is if you did not immediately consider the possibilities for polysemy. Watson Analytics for Social Media topic suggestions is design to call out these possibilities. As seen in the video link, the AT&T sporting event is called out within the topic suggestions so you can address this in your configuration.
So how do you correct for this problem? You have two ways to get to the data you want: context terms and exclude terms are a means to narrow the topic area. Exclude terms will remove conversations from the data set. Context terms require additional context to the data to be included. In the video there is a short list of context terms for each of the topics to ensure we are capturing the brand itself. As you add terms to the configuration, your topic suggestions should provide topics more aligned to what you want to capture for your analysis.
2. Open your mind to alternative vernacular.
When configuring your topics, consider the topic suggestions which expose you to a list of topics that your configuration is capturing. Are there words, hashtags or jargon that would allow you to better target your topic as well as expand what you are looking for. Using topic suggestions, you should see terminology that you can add to your include and context rules. Topic suggestions uses a sampling of data based on the settings in the project, such as date ranges, languages specified as well as sources selected. It is a good idea to try topic suggestions with different date ranges, sources to get as many suggestions as you can before running your analysis.
3. Determine how to breakdown the topics
What topics matter to you? If you want to compare the brands on author’s perceptions of pricing, then you should be adding a theme which captures conversations on pricing. As shown above, pricing can be identified many ways: bucks, dollars, price, cost, paid are some ways you may reference the pricing.
Pricing is a common perspective to analyze a brand, but there are many others for the Telco business: Quality of Service, Coverage, Customer Service, Loyalty, Plans, Bandwidth, Speed, Phones, Internet, Deals, Unlocked sim cards, etc… I am sure you can add your own. It is important to note that many of the topics listed here were not listed because they are a given, but in many cases, topic suggestions helped build the list. Building the list based on topic suggestions will reflect what people matter as it is a sampling of the actual conversations. Using topic suggestions for the themes can be quite useful to expand list of themes and the rules within each of the themes. In the video you will see the word outage added to the service theme as an example.
Other terminology you may want to put into the rules for quality of service would be along the lines of “dropping calls”, “static”, “dropped calls”, “my service” etc., Topic suggestions should also call out terminology from competitors which will allow you examine the perceptions of strengths and weaknesses of each of the brands. The sentiment can be different for the brands for given themes which magnifies the importance of themes.
4. Impact of the reports
In the video, we have multiple brands being analyzed. Including multiple brands is a good practice to follow as it provides a benchmark for high and low watermarks on volume, sentiment and other measures. The reports available within the social media project are great for doing brand analysis. It allows for head to head comparison on Share of Voice and Trends in the Share of Voice. You can quickly see which brand has the biggest mind share.
Again the theme breakdown really enables you to review the brands’ strengths and weakness. As the video calls out you can filter on anything in the data tray which makes this particular perspective valuable.
The sentiment report helps you with benchmarking the sentiments for each of the brands with can also be useful to capture the strengths and weaknesses of a brand.
The reports on Geography, Authors, Behavior and Demographics call out who the authors are when referencing the brands, where are they from, where do they communicate. This information will support a lot of the outbound activities to make sure the messaging is right for the target audience using the right social channels. The reports call out the brands’ influencers in the social space and these individuals/groups are key people you want to engage with to maximize your digital presence.
Current users of a brand are the life blood of brand so knowing what they are talking about is very important to understand. The theme breakdown helps the brand know what particular elements matter to the core customer.
5. Using Watson Analytics for more insights
When you run an analysis, you create a dataset within Watson Analytics. Using this dataset, you can create your own reports by asking questions about the social data that are not available in the default reports. You can review authors who are talking about being a prospective customer, or target the competitors’ audience who are talking about leaving the brand. Using the full features of Watson Analytics, you can choose different metrics (other than mention counts) such as follower counts, document counts, share counts for brands and themes and quickly put together your favorite visualizations within your own Watson Analytics displays.
6. Combine other data
Social data gets more compelling when view in context with other data. You can add other datasets to the mix, such as your CRM, Digital Analytics or e-Commerce data to glean more ideas on how go to market. Combining this data in a single view opens up new opportunities to answer questions relating to the “why” people are responding to the messaging, pricing, branding that we put into the marketplace.
At this point within the blog, you should having a better view as to how you can create a project within Watson Analytics for Social Media for brand analysis on Telecommunications companies. Similar approaches can be used for brand analysis on other industries as well. Try it out with your brand!