
While most companies engage in some type of analytics for their marketing efforts, some metrics become harder to track than others. While it’s easy, for example, to determine how many people clicked on an ad, it’s much harder to determine how many people exchange positive reviews by word-of-mouth. While companies can accurately get pieces of the picture, it’s difficult to understand what drove a sale, from customer awareness to first contact to after-sales behavior. Self-reporting, which has been the traditional means for uncovering intelligence, isn’t always accurate.
To help fill the gap, AI-powered lead intelligence solutions provider CallRail has announced AI-driven, self-reported attribution capabilities as a part of its innovation program, CallRail Labs. With this capability – for which a patent is currently pending – marketers and business owners can more easily get visibility into the impact brand, word-of-mouth, social media and other hard to track marketing efforts have had on generating leads, providing a more complete picture of marketing performance.
As mentioned previously, the original form of attribution was self-reported. However, as customer journeys evolved and became less linear, traditional methods struggled to capture this complexity. The introduction of call tracking software marked a significant leap in attribution, effectively addressing many of these challenges. The most impactful attribution reporting combines automatically captured, self-reported answers with call tracking reporting. When the two are used in tandem, marketers can fully and accurately read their marketing landscape and make confident, strategic and investment decisions.
”As AI continues to revolutionize industries, it has empowered us to unlock new frontiers in understanding and optimizing the buyer's journey," said Emily Popson, Senior Director of Growth Marketing at CallRail. "Until now, it’s been notoriously challenging to measure the influence of brand marketing, word-of-mouth, or dark social – that data was hidden in conversations. By bridging the gap between traditional attribution methods and AI-driven insights, self-reported attribution empowers marketers to make even more informed decisions and confidently navigate the complexities of today's marketing landscape."
Edited by
Alex Passett