Customer analytics refers to the technology and strategies that businesses employ to gain insight into their customers' behavior and make better business decisions, on the other side this analytics also can be delivered to their customers itself. Predictive analytics, data visualization, information management, and segmentation are examples of such techniques that are commonly utilized in direct marketing, site selection, and customer relationship management. Customer analytics' main purpose is to improve the overall customer experience from the business side, while from the customer side it can help users improve their content or activities inside the platform.
Some of the parameters that can be analyzed from this business include: social listening, bounce rate and pages, net promoter score, profile insight, session time, and many more. Tools used in customer journey analytics using customer relationship management platforms, customer service management software, sales platforms, Google Analytics, social media tools, email marketing platforms, campaign analytics software, data collection and management platforms, content management systems, and proprietary map metrics.
Providing customer analytics is able to help our customers to grow and develop in using our platform in terms of content, evaluation, and so onBy providing analysis about the activities of a user they can see the insights carried out. They will understand more about their habits and lifestyle choices, the more accurately a company can provide analytics, they may know what things need to improve their services based on users insight in the future scenarios. In detail, we will discuss this topic with Mr. Marcel Leonardo as Principal Product Manager of GLAIR.AI.
According to Mr Marcel, providing analytics/insights to our customers means we give information that was previously only known by us (as product/platform owner) to our customers, so that they have extra insight on what they do in the product/platform. The Insight can be descriptive data, or even predictive data depending on what we can provide and the methodology. Mostly about the use of the product owned by the platform owner to the user, which consists of the use and performance of the platform.
Examples of use cases that we can see from this activity like when YouTube is able to provide analytics to its users in the content they create, including frequently watched channels, number of hours, viewers, and the nominal fee they receive. The features provided include the pillars of YouTube Analytics, including: General Reports, Watch Time and Audience Reports, Engagement Reports, and Earnings Reports. Users can develop Top-performing videos in terms of views, watch time and audience and engagement, Content themes relevant to their target audience (think: how-tos, tutorials, vlogs, webinars), and How video details like thumbnails, titles and video length impact their video performance. Channel owners can see content activity that their viewers like as well as content that has high insight and engagement value. So that they are able to make improvements in the creation of much better content to gain high insight.
There are many benefits that can be obtained when we provide analytics to customers, not only from the customer side who is able to develop and know their activities. But from the company side, they can also evaluate the business services they provide to customers. This is also in line with the opinion of Mr. Marcel, according to him, customers can use analytics to learn more about what they've done with our product/platform, and they can track or make decisions about which features need to be developed or maintained. Customers know what they have done historically and what results they have achieved. From what they know, they can monitor and make decisions to improve their activities. In general, providing customer insight provides many benefits use cases including:
It's crucial to our customers so that they may profit from it and have a better understanding and data to help them plan their future actions on our platform.
Mr Marcel also added that providing customer analytics can benefit from two perspectives, business owners/platforms and users/customers. For customers themselves, data insight/analytics can help them to make decisions from the insights/data they get. In terms of companies/businesses, they can increase their value because they provide statistics to users, credibility in providing insightful analytics from appropriate performance (credible) to users, and can also provide feedback as potential features that can be improved from the platform from platform user input.
In line with that, providing analytics/insight to our customers play a role in developing our business. From Mr. Marcell perspectives, it can:
According to Mr. Marcell, the right time to implement a business is dependent on the industry. I'd say the majority of organizations provide Weekly Insights, with some providing Monthly Insights. However, some businesses that track and relate to money consumption will usually provide daily insights. On average, the most optimal is weekly. For example, project management software that gives weekly reviews of completed pursuits. It can also be monthly to see the performance improvement of the inter-month platform. You can also track daily, for example for advertisements.
Many teams are involved in developing analytics/insight within a company for customers. Data access depends on the company. From Mr. Marcel experience, it depends on credential access and the stakeholders involved.
There is some use case data that can be processed to generate insights for customers. The first one is to develop insight, this data is processed normally if for example it is only visual data. But for recommendations generally use Artificial Intelligence. An example of a use case is.
Back again to what kind of business. For example, for a content platform, what is certain is performance, which one gets the most likes and engagement.
According to Mr Marcel there are two challenges facing when providing customers analytics, the first one the challenge is mostly one of data-driven culture and mindset, which not every firm possesses. Most businesses are still unaware of how valuable data insight can be to their business and to their consumers. The second one is that the data structure and pipeline are not yet mature, despite the fact that we offer services to assist the organization in preparing an automated and clean data pipeline for analytics and other purposes, such as AI implementation.
To solve this challenge, of course, awareness and real action are needed in responding to it. The first is to instill a data driven mindset, that all the strategies we take are based on data. From this business, we can determine which features are continued and discontinued, and of course it's not just an assumption. The point is that the data speak not just an estimate. Second, at least there is data that is prepared even though it is raw data. So we can estimate what insights we want to develop. Now in this strategy we can use the services of a third party company to help data analytics to integration (3rd party), including GLAIR.
“Glair.ai provides managed / end to end service to help heavy lifting effort when customers want to provide analytics. Starting from understanding the data, preprocessing and data processing (effective and efficient query) until we visualize the insight and provide the dashboard, as well as the integration options.” Mr. Marcel added. The process uses cloud services and solutions that we have developed ourselves. Customers are usually given surveys first to help us understand their situation and which method we may take to deliver analytics. GLAIR's services consist of leveraged services in the cloud, which can assist in data extraction, tools developed in-house for understanding, processing, and visualization of data, on the customer side, they can provide questionnaires, and see which approach they want to provide. to adaptable customers.
In the last session, Mr. Marcel advises to our readers that analytics and insight are normally not a top priority, but if we notice global trends, it might become a game changer in addition to essential features, as it will benefit both sides (US and our customers). If we don't think analytics is a top priority right now, we can at least adopt a data-driven approach and prepare the company's data structure for when we do want to use analytics, before it becomes mainstream and we fall behind. If you believe analytics is crucial but you still need to keep up with key features, don't be afraid to delegate the analytics work, as developing an analytics staff from the ground up is not cheap or easy”
Currently providing insight to customers is able to bring benefits from the customer side and from the company side. The benefits are two-sided and are able to facilitate people in developing the services used.