“Personalization will be the prime driver of marketing success within five years,” McKinsey predicted, and for good reason. It’s simple: Personalization improves customer satisfaction, keeps users engaged, and increases retention rates.



You know users are starved for time and face too many competing priorities. Removing the work a user needs to put in to get value out of a product makes them more likely to use it.&nbsp;



In this article, we’ll explore three ways you can build a more personalized analytics experience for your customers and end users. First, though, let’s get on the same page about what personalization is.



The right data visualization will take your custom analytics to the next level.



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<h2>Defining personalization — a key to analytics success</h2>



Gartner defines personalization as &#8220;a process that creates a relevant, individualized interaction between two parties designed to enhance the experience of the recipient.” The takeaway for app builders is obvious: The experience you’re creating should be based on information and preferences that you know about the individual.



This information could be basics like the organization or group they are a part of, or as detailed as their color preferences (think, application skins or avatar images) or their preferred actions and behaviors on your platform (like Netflix or Amazon recommendations). Sisense Smart Recommendations is a good example of personalization during the dashboard design process. Based on design history, the system will recommend relevant fields as the designer is building, saving time and effort.



Beyond personalization, customization is giving your customer or end user the ability to make their own changes to the experience (e.g., setting their own custom colors or UI skin in an app or video game). Designers and engineers can <a href="https://www.sisense.com/blog/data-visualization-libraries-to-enhance-your-custom-analytics/" target="_blank" rel="noreferrer noopener">add a new visualizations</a> or build <a href="https://www.sisense.com/blog/infusing-analytics-workflows-salesforce-lwc/" target="_blank" rel="noreferrer noopener">integrate actionable intelligence into a CRM</a> to suit unique business and end-user requirements.&nbsp;



In an analytics platform context, there are two layers: (a) how the platform personalizes and enables customization for the builder and (b) how the platform enables the builder to deliver personalization and customization to the ultimate end user or customer.



As a provider of analytics solutions, let’s dig into some ways you can deliver a personalized experience to your end users and customers.



<h2>Matching look and feel&nbsp;with ease</h2>



A seamless user interface can go a long way in reducing friction for end users or customers and enhancing the user experience. Customizing the UI across the board is the first step; personalization takes it even further.



Say you are delivering analytics to several customers, departments, or teams: You can tailor the look and feel, including the colors of the analytics view, to each group either based on brand colors or a preference. If you are infusing analytics into an application where you enable the user to select their own themes, then you want to ensure that your entire application caters to their preferences, including embedded analytics.&nbsp;The right customization capabilities (like <a href="https://www.sisense.com/blog/personalizing-the-analytics-user-experience-with-sisense-themes/" target="_blank" rel="noreferrer noopener">Sisense Themes</a>) within your embedded analytics software will enable you to change the look and feel of your analytics so you can tailor the experience to each of your customers and groups of users. 



<figure class="wp-block-video"><video autoplay loop muted src="https://cdn.sisense.com/wp-content/uploads/themes-2-vid.mp4" playsinline></video></figure>



<h2>Building an effortless personalized insights journey</h2>



Time to insights and ease of use are important factors when it comes to increasing analytics adoption, which ultimately leads users to make better decisions.



However, not all users have the know-how or the time to find the insights they are looking for. Sometimes, they might not even know what they want! This is where personalization and automation can be transformational. Today, AI and machine learning can help users make the jump from self-service to truly data-savvy via suggested paths. Leveraging these capabilities creates a personalized experience for your end users and customers, which can reduce your workload and create better experiences for your customers — it’s win-win!



Take, for example, <a href="https://www.youtube.com/watch?v=ubqsDICqquQ" target="_blank" rel="noreferrer noopener">Sisense AI Exploration Paths</a>. This capability automatically recommends suggested discovery paths that anticipate your viewers’ questions without requiring a dashboard designer to create more widgets based on the data model that the dashboard is built on. <a href="https://documentation.sisense.com/latest/content/nlq.htm#gsc.tab=0" target="_blank" rel="noreferrer noopener">Natural language querying (NLQ)</a> features can makes smart recommendations that guide viewers to ask better questions based on what the system has learned already; similarly intelligent features can help identify key drivers and root causes so users can make better decisions. <a href="https://www.sisense.com/blog/how-knowledge-graphs-boost-the-benefits-of-analytics/" target="_blank" rel="noreferrer noopener">Knowledge Graphs</a>, siting in the back end as an enabler of queries and recommendations, provide an efficient way to ask questions of data, regardless of technical skill.



<figure class="wp-block-image size-full fancybox"><img src="https://cdn.sisense.com/wp-content/uploads/AI-Exploration-Paths-1.jpg" alt="" class="wp-image-119936"/><figcaption>Sisense AI Exploration Paths</figcaption></figure>



<h2>Unleash your team&#8217;s creativity with personalized experiences</h2>



Personalization empowers you and your team to get creative with how you build your analytics. This could be something as simple as tailoring dashboards to suit specific teams or departments or more involved initiatives like building an analytics view on the fly based on a set of questions you ask the user.



In one example, Seismic built <a href="https://seismic.com/company/blog/fall-2020-release-content-analytics/" target="_blank" rel="noreferrer noopener">role-based dashboards</a> so each type of persona (chief revenue officer, content owner, chief marketing officer, etc.) gets the content relevant to them. In another example, a large fleet management software provider populated a personalized collection of embedded widgets (leveraging the Sisense.JS embedding library) at run-time based on a few discovery questions asked of the user at the top of the experience. In another simple, creative example leveraging Sisense BloX, you could even build a personalized dashboard <a href="https://support.sisense.com/hc/en-us/articles/360048260954-How-to-create-a-Personalized-Navigation-Landing-Page" target="_blank" rel="noreferrer noopener">navigation page</a> that surfaces the most popular dashboards to the user.&nbsp;



Whatever type of personalization makes sense for you and your company, it’s time to start thinking about how you can bring your application closer to the viewer and how you can make your app and your analytics more useful and easy to use for your audience. The good news is that advancements in technology, including AI and machine learning, low-code/no-code capabilities, and open extensible platforms, mean that there are more and more options today to make it happen. The only limit is your imagination.



Make in-depth personalization a snap for your dev team and evolve your application and your business



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Former Sisenser Shruthi Panicker holds a BS in Computer Science as well as an MBA and has over a decade of experience in the technology world.

Three Ways to Personalize Analytics to Improve User Experience

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