Many business owners and department heads have heard of Artificial Intelligence, \u201cMachine Learning\u201d and predictive models, but aren\u2019t quite sure how these technologies could apply to their business. Today there are solutions that let you know, for example, which customers will stop paying, which will cancel or which will see a significant drop in revenue, and they aren\u2019t expensive services but accessible to every company. Using them in the coming months will largely determine the ability to emerge from the recession and be efficient and competitive in the market.<\/p>\n
Most companies\u2019 information systems rely on traditional reports from their ERP and CRM management applications, or even Business Intelligence solutions.
\nWith them, they can get reports and dashboards with historical data to analyze company performance and trends across different business areas.
\nThese tools are great and have been essential for many years, but they only provide information about the past. Today you can take data analysis a step further and get predictions about the future through customized predictive models.<\/p>\n
Being able to make decisions knowing what will happen in the future \u2014which products we\u2019ll sell, what the repeat rate will be, which customers will default, how much my customers\u2019 revenue will fall\u2026\u2014 provides key insight for running the company more rigorously, especially in difficult times like the ones we\u2019re living through.<\/p>\n
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In every crisis, most companies in every sector will suffer an economic impact that mainly shows up as revenue drops<\/strong> and customer loss.<\/strong><\/p>\n For both, there are solutions based on predictive models that can significantly help minimize the impact.<\/p>\n Revenue drops and customer loss<\/strong> These predictive models forecast the churn risk of customers \/ subscribers \/ students \/ users \/ members\u2026 depending on the sector.<\/p>\n The risk can simply be \u201cthe probability that a customer will cancel\u201d<\/strong> in subscription business models, or risk can be defined as potential customer \u201crevenue drops\u201d<\/strong>:<\/p>\n The model shows the average revenue loss<\/strong> for each segment over a 1-year horizon, as well as the individual values<\/strong> for each customer.<\/p>\n With these two models, companies gain very powerful tools to face the crisis and the subsequent recovery, and can launch and focus the most appropriate sales, financial and marketing activities and decisions from minute one. The democratization of these solutions makes them accessible to all kinds of companies, since they are subscription services (SaaS) at very reasonable prices, with implementation projects taking just a few weeks.<\/p>\n To paraphrase Darwin, we can say that in the current economic climate \u201cThe companies that survive will not be the biggest or the most powerful, but those best able to adapt to the circumstances of the pandemic\u201d<\/p>\n Relying on data for decision-making is increasingly the way to improve efficiency and adapt your eCommerce business to change. Being able to adapt quickly and know how actual activity will perform through predictive models is a tool with extraordinary potential for tackling the recovery.<\/p>\n Running a company on historical data that has lost all its value and relevance is not the same as relying on constantly updated information, based on machine learning technologies that learn on their own and quickly adapt to circumstances that are more changeable today than ever.<\/p>\n To survive and accelerate, it\u2019s crucial to know what will actually happen (with its variations and alternatives), not what happened before or what procedure seems to dictate should be done.<\/p>\n With this privileged information we can steer the company toward its goals and base our decisions on science rather than gut feelings, opinions or past data. Acting with urgency<\/strong> is also important, because the democratization and cost of these solutions make them accessible to everyone, and falling into \u201canalysis paralysis\u201d will only leave you less prepared and competing at a disadvantage.<\/p>\n","protected":false},"excerpt":{"rendered":" Many business owners and department heads have heard of Artificial Intelligence, \u201cMachine Learning\u201d and predictive models, but aren\u2019t quite sure how these technologies could apply to their business. Today there are solutions that let you know, for example, which customers will stop paying, which will cancel or which will see a significant drop in revenue, […]<\/p>\n","protected":false},"author":2,"featured_media":14419,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2519],"tags":[],"class_list":["post-19000","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"yoast_head":"\n
\nWe\u2019ve found this is a common concern for every company, and introducing artificial intelligence can mitigate it significantly.<\/p>\n\n
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\nThe two points above are just clear examples that address very common concerns right now, but there are many other business areas that can be optimized with predictive models.<\/strong> Here are some examples by sector:<\/p>\n\n
Key concepts for economic recovery: efficiency and adaptation<\/h2>\n
\nIt\u2019s in this context that the two concepts mentioned at the start, efficiency and adaptation<\/strong>, matter more than ever.<\/p>\n\n