Marketing budgets are often one of the first to be cut in times of economic downturn, with a Gartner survey reporting record low marketing budgets in 2021 following the pandemic. With the current pressure of a potential recession on the horizon, marketers need to think creatively to find new ways to support revenue and company growth despite potentially lean budgets. On top of that, companies need to be able to adapt quickly to changing consumer preferences and behaviors toward different products, channels, campaigns, and prices. This combination of factors makes it more challenging than ever for marketers to achieve the most of their ad spend while being agile and making better business decisions that address changing customer demand. One solution to those challenges? Decision intelligence?
Decision intelligence is a different approach to analytics that connects various data sources together and applies analytical and machine learning automation to give a complete picture of what’s happening in the business, why metrics are changing, and how to drive business outcomes in granular ways. The technology offers a way to bridge insight gaps, helping any type of user–from advanced data scientists to less technical marketing leads–make data-driven decisions at scale with continuous and evolving improvements. Despite the threat of a potential recession, decision intelligence can help marketers generate AI-powered insights that can be used to gain a deeper understanding of the customer, optimize advertising, and increase customer lifetime value.
Gain a Deeper Understanding of the Customer
Traditional business intelligence focuses on reporting and dashboards of KPIs against simple dimensions. But in today’s world, customers are multi-dimensional and the data surrounding customer engagement and behaviors are complex. Data analysis requires generating and testing hypotheses across every dimension to find the most impactful combination of attributes that contribute to desired business outcomes. Decision intelligence pulls different data sources together—including transactional, sales, market share, advertising, and more—and analyzes every dimension to give marketers a comprehensive view of the customer. These automated insights are delivered in a single pane to empower users to better understand customer preferences, how they change, and where there are areas of potential growth that can be capitalized—breaking down existing information silos within organizations and empowering marketers to find insights across every available data source.
With a deeper understanding of the customer base, marketing teams can identify gaps in untapped markets that can be shared with the company to increase revenue. Although this may seem like a daunting task, decision intelligence automates the time-intensive manual analysis of data that teams previously had to manage by hand. Having an engine proactively uncover findings across every customer data point streamlines the analytics process and gives marketing teams more opportunities to identify growth opportunities, including ways to optimize advertising efforts and increase CLTV.
Optimize Advertising Efforts
According to data from McKinsey, 71% of consumers expect companies to deliver personalized interactions and 76% get frustrated when this does not happen. Unfortunately, a Gartner study found that 63% of digital marketing leaders struggle with personalization, and only 17% use AI and machine learning tools to help reach their target audiences.
Although identifying different customer segments based on interest, previous purchases, and age makes sense, it can be extremely challenging to find the segments that will have the most impact as there can be hundreds, if not thousands, of combinations that marketers need to analyze. On top of that, most AI and ML tools require advanced data science support and hiring that talent can be costly and time-consuming. As a result, data analysis performed today can be more biased and limited than organizations want to admit, which is not a recipe for staying ahead of the market—especially when customer preferences change frequently (for example, less spending during a recession).
Decision intelligence can go deeper than traditional methods, using automation to efficiently analyze large data sets. These data sets can then help create customer segmentation that encompasses financial well-being, spending habits, political attitudes, personal values, and more. With these key customer segments, marketers can optimize their campaigns to reach the core audiences most likely to buy their products or engage in their services. Decision intelligence can even take these segments a step further by empowering marketing teams to create an individual approach to each customer segment. This level of insight also supports predicting customer churn, cart abandonment rates, and consumer intent to maximize ROI for each customer segment.
Increasing Customer Lifetime Value
Customer lifetime value, known as CLTV or customer LTV, represents the amount of money a customer would bring to the brand during their entire time as a paying customer of the business. CLTV tells companies the value of a customer and helps them decide how much they can invest to retain them. Higher-valued customers tend to make repeat purchases, while others may not return at all.
Using machine learning and automated analysis, decision intelligence uncovers the behaviors and signals of the most loyal customers that may not be as obvious when looking at static data. Decision intelligence helps discover small, more granular customer populations to place insights directly with analysts and business teams. Determining CLTV with decision intelligence accelerates customer retention by helping marketers identify customers who are easy to retain and develop the proper marketing strategy, such as offering incentives to repeat customers through communications that encourage spending, either by buying frequently or buying more (or both). Ultimately, the technology provides greater, faster insights that support targeted marketing campaigns, leading to increased profit opportunities.
Although customers may be wary of spending in a recession, decision intelligence can help marketers determine the best way to reach them. Tapping into core audiences and markets, gaining a deeper understanding of customers, and enhancing CLTV are instrumental strategies in creating the best campaigns that deliver on revenue and customer satisfaction—even when spending is down.
