Ephemerata

Reference Service Plan

Competitive Intelligence Service

Description

I serve as the primary curator for a digital library used to provide reference services on the competition to the field sales personnel. The library provides an online, remote reference service to sales personnel seeking information about how the competitor’s products work (or don’t work); how they are sold, pricing models and discounting practices; and what false information and rumors are being spread by the competition in the effort to entice the prospect to buy the competitor’s product. Additionally, the library conducts data analyses, research projects, performance assessments, community resource audits, and collection assessments. The library also hosts a website for the commonly asked information and currently boasts over 10,000 subscribers with recent (less than 6-months old) subscriptions.

The Competitive Intelligence team provides actionable information to its primary constituency – field sales teams. To support the primary customer – salespeople – the CI team provides a wide variety of types of information. Recent analysis shows that an informed salesperson can increase their probability of a sales ‘win’ by 10 percentage points over their lesser informed counterparts, along with a shorter sales cycle and a higher average deal size. It is this observation that drives much of the value proposition of the reference service.

We often respond to requests for information which either force an update to an existing information product or a review of a given datum. Sales teams often request information about the competition and their likely sales strategies. Typical questions may be posed, as shown in the list below:

  • What are the typical pricing tactics used by the competition and what is their approach to discounting?
  • What are the sales messages typically communicated or positioned about the competitor’s product (in effect, their claims as to why they are better)?
  • What is the competitor messaging about our products (in effect, what are the competition’s claims as to why my company and product is not the optimal choice)?
  • What are the predispositions of the various members of the customer team?
  • What do they [the customers] believe? Who are their favorites? Why might they think that way?

Type of Library

With over 10,000 subscribers, who live in more than 80 countries servicing the IT needs of companies on 6 continents, the reference service have to operate on a remote/virtual basis. Users are introduced to the reference service during their new-hire onboarding process, with annual retraining delivered electronically. Additionally, the reference service conducts outreach programs to make new users aware of the service, to survey the needs of the community, and to assess the information products produced by the service.

The answers to these questions allow the sales-person to begin to understand what perceptions may exist within the buyer’s mind and to develop the thoughtful responses needed to challenge those perceptions and to form a persuasive argument.

The technical sales engineering teams often request information regarding specific technical details of a competitor’s product which they need to provide a solid foundation for their analytical assumptions. Sales analyses typically consist of some form of financial justification, either a cost-benefit analysis or a risk-mitigation analysis. A competitive intelligence team provides the technical and go-to-market details regarding the competition which then form the basis for any economic assumptions of cost or calculations of risk impact.

Target Audience

The typical field sales team that focuses on Fortune 2000 companies may consist of several distinct sales specialists, several technical sales engineers, and other personnel, often referred to as “overlay sales”. My company focuses on Information Technology (IT) and has a vast portfolio of products with which to address this $3 trillion market. Due to the plethora of products and solutions that the company provides and which customers demand, no single sales person can possibly address or manage the entirety of the set of offerings needed for a given customer; which gives rise to the idea of “overlay sales”. There is one account manager responsible for the customer account. They rely on the overlay sales teams to provide the needed specialty expertise needed to address the customer’s needs. This can be likened to the idea of a primary care physician, who uses specialty doctors to assist in providing care beyond their skill set.

Other teams, such as product management, product marketing, etc., also often consult the Competitive Intelligence reference service looking to make a ‘data-driven decision based on the following: Market Trend Analysis, which includes industry analyst information, and which is distilled into a prognostication of the types of emerging problems about which customers are starting to become concerned and for which they will spend money; Buyer Pattern Analysis, which is the creation of a “persona” that typifies the set of personalities involved in a corporate purchasing decision of our technology and allows the sales teams to develop specific ‘approach strategies’ for these people; and Pricing Recommendations, which reflect the historical trends of our sales discounting practices compared with any changes from the competition – such as new pricing models or patterns or the bundling programs of new and emerging products and vendors trying to disrupt the marketplace – and result in changes to our list prices, our licensing models, and possibly our revenue recognition strategies. The Competitive Intelligence Service collects this information and makes it available to all users.

Desired Outcome

A reference service must be able to serve as a central information point for its customers. It will act as a services bureau, able to connect a person with a query (a business question) with someone who could help them answer that question with data. The primary activity here is not casual “what if” questions but to help someone seeking to develop insights, using the data, which will help change the way they do business. Once the business person is able to answer “what they will do with the answer”, a library docent/data specialist (we call them subject matter experts or SMEs) is able to better help them find and visualize their answers. Thus, the primary audience will be employees and staff of the corporation; often referred to as knowledge workers, these people tend to execute the functions of the business according to established processes and protocols. Improving the way they do business or ceasing an action that adds little to no value is the object of these ‘questioners’.

Measurable Outcome

The primary goal will be to increase the usage of the Competitive Intelligence Service. That will be measured by using visitor metrics, particularly returning visitor metrics. Also, while we hope to decrease actual questions of the staff by using a FAQ-style information portal, accession of the various questions will serve to provide an indicator of question interest. Therefore, accessing a question link will also indicate a question asked. FAQ access rates, increased access of the various questions, and usage of the links from the FAQ should increase over time, even among returning users. The section below identifies some of the library’s main metrics for operation and valuation. Since social media is ultimately intended to drive awareness of the library and its value proposition, the metrics for any specific social media will focus on the users’ activities:

  • The time between a user’s initial visit and return visit.
  • The increase in return visit frequency, if any. That is, a user should return to the library more and more often.
  • The number of “touches” that are achieved through social media – visits from a referring site, such as an internal wiki or the employee intranet sites.
  • The number of “touches” that are achieved through social media – visits from a referring site, such as an internal wiki or the employee intranet sites.
  • Social media announcement campaigns, including announcements by executives at employee meetings describing the achievements by employees when using the library.
  • The number of incoming referral links from other employee intranet sites over time.

Data Evaluation Plan

To determine if the library is adding value to the corporation overall, it will need to be evaluated on a continuing basis. Since this is a digital library, it is reasonable to instrument the library according to the value propositions previously articulated and to create dashboards visualizing the library trends. The value propositions set forth in this plan drive the key metric definitions:

  1. Increased reuse of datasets within the library for data science projects, including partial dataset reuse. “Forking” of a dataset with subsequent joins to new data would be considered a value-add dataset.
  2. Increased dataset submission to the digital library
  3. Increases (over time) of visitors/return visits
  4. Increased data visualizations that result in business change. An example of this would be encouraging the sales force across two divisions to prefer to work together and cross sell more of the company’s portfolio (sometimes referred to as, “increasing product drag”).
  5. Decreases in the time a typical data science project spends on data collection and cleaning due to curated data from the library
  6. An increase (over time) of the questions submitted to the library

Dataset Key Metrics

Primary and secondary metrics for the library are those that address the questions from the evaluation list just described. An example of metrics for item 1 would be:

  1. Increased reuse of datasets within the library for data science projects, including partial dataset reuse. “Forking” of a dataset with subsequent joins to new data would be considered a value-add dataset.
  • Number of new, raw datasets submitted to the library; trended over time
  • Number of new datasets with additional use cases added; that is, new data derived from existing data but used for a new purpose; trended over time
  • Number of existing datasets joined with new raw data to create a curated dataset for a new use case; trended over time
  • Number of new use cases added to the library
  • Number of projects finalized using library data
  • Number of projects ‘extended’ / reopened using library data

The number of questions could be nearly endless, so it is incumbent on the library directors to decide which questions drive value to the company at large and thus affect funding and resource budgets. To the degree that the questions help the library engender a positive return on investment, then the questions should be investigated and charted. Questions that do not help the library should be ignored.