Using Earning Intelligence (EI) to improve marketing, sales, and strategies

Published Date: 2019/09/14

There are over 4800 earnings call transcripts provided by chief executives of public companies every quarter detailing the rationale behind their strategies, operations and earnings. Often times, it explains the dynamics of the market space, consumer behavior, and regional strength and weakness on products and services. Statisticians and data scientists have tried and failed to turn earnings semantics with traditional statistics, machine learning or deep learning techniques into intelligence. The reason of these failed attempts is because subject covered by these earnings calls are non-repetitive, new and unique, and causations are comprised of permutation on almost infinite number of entities and criteria.

One approach that works since the beginning of earnings calls is the analysis by experts. When experts read these reports, they use their expertise to interpret semantics on strategies, operations and earnings results. Investment firms, economist, marketing teams and executives alike have been using this approach to better their perspectives and decisions. Unfortunately, the time and cost of manual processing make this approach not scalable and cost prohibitive.

EI uses artificial intelligence based on Symbolic Logic to emulate this manual process. It is a close resemblance of the above mentally challenging process. A three steps approach enable EI’s AI machine to analyze earnings call transcripts like a human analyst. The first step is to gain a perspective of subject matters discussed in an earnings call transcript. The second step is to narrow the perspectives by subjects of interest. The third step is to take a deep dive into the details as presented by the executives on the subjects of interest. User of EI would take the information to formulate a strategy as depicted in the four steps.

Using a process of Natural Language Understanding (NLU), EI weights each of the subjects by categorizing it into three groups, i.e., momentum, challenge, and work-in-progress. The following is a brief explanation of each group:

  • Momentum - Impact to business that are subject to strategic response which affects growth and revenue potential
  • Challenge - Facts and events that are pivotal to the business operation which could affect outlook, revenue and cash flow
  • Work-In-Progress - Ongoing operational related matters
  • These results enable users to compare business activities between companies and to identify targets based on their need. For examples, a marketing team may look at companies of certain sector and industry that have lots of momentum and challenge as a candidate in developing sales leads, a sales team may read the detailed excerpts to develop a sales strategy, a service provider may seek out companies with lots of work-in-progress to offer out sourcing as a service, an economist may use the metrics to compare the weakness and strength of sectors and industries.

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    This article draws references from Earnings Intelligence, a service provided by SiteFocus