With rising consumer expectations for personalization across the entire customer buying journey, the ability to understand consumers in real time is increasingly essential to the long-term success of a brand or retailer. It’s also the key for brands to demonstrate that they really understand the consumer and anticipate their needs by serving up highly personalized and relevant content and offers when a consumer is showing intent to make a purchase decision – which is demonstrated by their actions and behaviors.
Understanding consumer intent is key to optimizing customer engagement across interaction touchpoints and increasing customer lifetime value. By connecting marketing interactions to consumer intent at the very moment it’s being demonstrated helps brands remain competitive. It increases the efficiency of digital advertising investments, and enables a brand to deepen a relationship with a customer at the point of interest.
Going Deep with Intent Signals
Measuring intent is highly personal and data-driven, based on correlating previous and current transactions, preferences, and behaviors to provide insights into a consumer’s interests that indicate potential intent to take action. It’s about mining a customer’s digital trail of indicators that can be leveraged as data sources (first-party, second-party, and third-party data) to detect and understand intent in the moment of interest.
The challenge for brands is that the consumer buying journey is multi-event across multiple devices (desktop to mobile device to retail store to call center). To capitalize on real-time intent signals, brands must have capabilities for real-time data activation, real-time cross-channel identity resolution, and real-time data onboarding to connect offline and online data.
To properly gauge intent, data must provide full context. A single customer view that combines every source of customer data (streaming, batch, structured, semi-structured, unstructured) into a golden record tells us everything there is to know about the customer, their device and channel preferences, buying patterns, and transactions. Combined with the knowledge of the customer’s precise moment in a dynamic buying journey, this provides the necessary context that gives meaning to real-time intent.
A Real-Time Response Unlocks the Value of Measuring Intent
Prioritizing consumer intent shifts the marketing mindset from pushing static messages to instead engaging a consumer based on intent signals, leading to higher relevance. It requires the continual listening and mining of digital cues to inform a real-time response as signals dictate.
According to a study from McKinsey, traditional marketing communications that are aligned with a calendar of holidays, product launches and other marketing-defined events is an “unresponsive model organized around the company, not the customer.” The study finds that brands must organize around the customer’s circular decision-making process that consists of four phases: initial consideration, active evaluation (research phase), closure (actual purchase), and post-purchase (customer experience) period.
Omnichannel intent listening connects a brand with a customer throughout each phase. It improves the customer experience while lowering the cost of interacting with a customer because it curates offerings that respond to desire (interest) rather than indiscriminate engagement.
To do it right, however, entails far more than aggregating every piece of customer data from online and offline channels (in-store, website, mobile app, social). Exploiting intent signals requires a real-time decisioning engine that intelligently orchestrates a next-best action or recommendation for the customer at the moment of interaction – targeting a customer by who they are and what they are doing at a specific moment.
Real-time decisioning factors intent intensity, which is a recognition that not all intent signals are the same. There are behavioral, event-driven, and variable signals, as well as those that are affinity driven, and transactional. A collection and organization of all signal types to better identify changes in frequency and intensity is known as intent monitoring; spikes in intent indicate that a customer or target account is active in the market, which marketers can exploit with pitch-perfect relevance and context in the cadence of the customer journey.
Expanding the Last Mile
Brands often limit their view of consumer intent to a single digital channel only view or to the channel that was the last mile to the consumer where a purchase was finalized. There’s a tremendous amount of value in understanding every customer interaction and how each interaction affects the next stage in the journey and the eventual purchase decision. Brands must understand the entire customer journey on the path to purchase (digital and traditional) in order to optimize it. Without customer journey data that spans from anonymous to known customer engagement, there is no way to fully take into account intent or attribution to recommend the next best actions with each unique customer over time.
Intent-based marketing powered by real-time decisioning generates actions that, for the customer, feel relevant and natural and give them the feeling that a brand knows them as a unique individual. It’s a powerful feeling that customers reward with a greater share of wallet. McKinsey estimates up to a 20 percent sales boost from data-activated marketing that is based on a person’s real-time needs, interests, and behaviors.
That is a powerful incentive for brands to finally make the shift from a calendar or transaction-based marketing strategy to one that is organized around the omnichannel customer.
