Movies and TV shows are great at establishing narratives, hooking the audience into that narrative, and leaving them wanting more. This is the reason why we flock to theatres and spend hours binging entire TV series.
Would you believe me if I told you that one function in your business follows the same process as films and has the same power to engage its audience? Well, it exists, and it’s called marketing.
Ask any passionate marketer and they will tell you that marketing is an art. An art that requires creative marketers to weave narratives that address the pain points of consumers.
They would also tell you that the process is all about exploring the relationships between an action and its effect, just like in movies or TV shows.
While traditional marketing involves a lot of guesswork and trial and error, this process does not work in the contemporary market. In the modern business landscape—in which one wrong move can lead to significant ramifications—guesswork and trial and error is not enough. Marketers will need more than a good hunch to succeed in the market.
To be more precise, marketers need the power of data analytics to be successful. With SAS visual analytics, you will have the tools you need to share a meaningful story with your audience.
In this post, we will explore how SAS visual analytics on Viya can help marketers improve their strategies.
One of the important skills any marketer can possess is understanding the relationship between the actions of a consumer and their reasons for performing those actions. This allows for the creation of impactful marketing strategies.
To do this, companies collect large amounts of data and analyse them to establish connections between each variable. All data analytics tools are great at doing this. Only some of them, however, present the data in a way that is easy to comprehend.
SAS visual analytics on Viya excels at presenting the insights in a digestible way by using visual data tools such as bar graphs, charts, heat maps and many more. By doing this, visual analytics tools allow marketers to understand the relationship between variables easily and make better marketing decisions.
The success of a marketing campaign relies on its messaging. Marketers should focus on the main pain points of their audience through their messaging to make a meaningful impact. This is easier said than done.
To deliver an impactful message, marketers need to understand the preferences, behaviour, needs and wants of their target audience. Although it is possible to build comprehensive customer profiles using text-based data analytics tools, visual analytics makes the process simpler and faster.
With SAS visual analytics on Viya, marketers can centralise every piece of information they have about their customers in one visual profile. The advanced tools built into the platform makes presenting overall statistics of the target audience, or the individual profiles, easier.
Using these customer profiles, marketers can optimise their messaging to deliver a much larger impact.
In traditional marketing, marketers know the success of their campaigns only after they are taken live. This means that if bad marketing decisions are actioned, the marketing campaign will fail to connect with the audience, and there will be no way to prevent these events from taking place.
Advances in machine learning and data visualisation, however, allow marketers to simulate their marketing campaigns and predict the outcome. This helps marketers take a trial and error approach to their strategies without hurting their sales figures.
Marketing is about manipulating consumer pain points to deliver a narrative that prompts them to follow up on a campaign’s call to action.
In this day and age, to be successful, a marketing campaign must utilise the wealth of information available to them. SAS visual analytics on Viya can help marketers do just that.
With the power of data visualisation, marketers can deliver meaningful messages to connect with, and engage, audiences in the long term.
I have worked with a lot of businesses over the years, and I have seen an interesting shift in their marketing strategies. Most organisations are now looking to maximise customer lifetime value (CLV), rather than just focusing on acquiring new customers. There are several reasons behind this trend, but one cause is technology, like SAS visual statistics.
Businesses spend a lot of time and resources on customer lifetime value (CLV) and with good reason. Research shows that when customers are happy with their experience, they spend more money on subsequent purchases, raising revenue, while reducing customer acquisition expenses.
Businesses have tried to improve customer retention using strategies like social media campaigns and niche buyer personas. However, one of the most effective strategies for improving customer lifetime value has been data analytics. According to a study, over 52% of companies and 50% of agencies stated that smarter use of data analytics is the most effective strategy for improving CLV followed closely by customer segmentation and more precise buyer personas.
One reason why analytics platforms have proven to be incredibly effective is because of the level of insight data analytics grants organisations. Platforms, like SAS Visual Analytics, can breakdown and present customer data in a way that is succinct and easy to understand, while also revealing trends that are hard to identify.
Let’s take a deeper look into how SAS visual statistics.
SAS visual statistics is an effective tool for maximising CLV because of its ability to comb through data and use it to build predictive models like dynamic group-by processing, descriptive modelling, in-memory processing and flexible deployment options, all essential options for building predictive models. Predictive models that will provide businesses with insight into customer lifetime value.
The ability to dynamically explore datasets and predict future trends makes it easier to resolve problems. For example, if a business discovers that revenue fell compared to the previous year, they can breakdown data based on a specific variable to better understand the causes. Furthermore, it is possible to build multiple data analytics models, like linear regression data models and gradient boosting models, to better compare which output is more accurate.
One of the most useful benefits of SAS Visual Statistics is the incorporation of AI into the model for sharper analysis, making it much easier to breakdown a large volume of data relatively quickly.
The option to breakdown data based on different conditions eases the process behind maximising CLV because businesses have an easier time studying the data in a different context.
The new context can reveal problems not found before, making it easier to better understand the factors contributing to (or discouraging) CLV. The ability to dive into big data and identify problems quickly is one reason why organisations believe analytics platforms are an effective method to maximise CLV.
Thanks to SAS Visual Statistics, most businesses find it easier to identify the underlying causes that propel or hinder the lifetime value of a customer, causes that are not so readily found using other methods. Given the immense volume of data most organisations are dealing with, most businesses can save a lot of time and resources when optimising efforts to improve CLV.
One of the biggest benefits behind SAS visual analytics compared to other methods is that insight gained can improve operations in multiple areas. Whether it is smarter marketing campaigns, cost optimisation or improving retention strategies, the insights generated from SAS visual analytics can help businesses for years to come.
SAS Visual Statistics is an excellent tool guaranteed to generate tremendous ROI in the long run. However, there is no denying that it is going to take a substantial investment to get the platform to work. This is because SAS Visual Analytics requires expertise to be properly installed and integrated into business operations.
While there is no denying that SAS Visual Statistics is easy to use (even people with a non-technical background can use the platform) you still need the support of SAS specialists to integrate the platform into operations and maintain it. Working with the right team can help businesses optimise their operations to cut costs while still looking for ways to improve CLV.