Ends on February 18, 2018

The Marketing Science Institute (MSI) is pleased to announce a call for submissions to the 2018 MSI-Juniper Networks Research Initiative. MSI and Juniper Networks, an MSI member and the industry leader in network innovation (NYSE: JNPR), are working in collaboration to share B2B data with select teams of researchers to address questions of interest common to Juniper and the scientific community. Researchers are invited to submit proposals by February 16, 2018 and selected teams will be notified by March 19, 2018.

A data overview, potential research questions, and description of the submission and selection process are provided below.

In addition, on January 17, at 10:00 AM PST Juniper Networks will host a presentation and Q&A session (see invite) to review the underlying data infrastructure and connected data, and to provide a high-level review of the content used by the organization.

To submit your proposal, please scroll to the bottom of this page.

Data Overview

Juniper Networks’ marketing organization has adopted a data-driven strategy to understand the full customer journey (i.e., the sequence of customer interactions with the firm leading to purchase). To understand this process, we built a marketing data lake called Verity that integrates several sources of data from advertising logs to web logs to Salesforce.com to purchase data. By using a proprietary technology to merge different data streams, we are able to monitor and track the purchase decision-making steps of a customer.

In high-value B2B tech sales, purchases are made by accounts that comprise many influencers and decision-makers, all of whom are captured in the data. When decisions are made by accounts, a focus on an individual would be incomplete. Our focus has been on understanding the customer, or account so that we can determine how to assess marketing ROI, and determine how to allocate budget effectively across the marketing organization. We expect that the data have the ability to be prescriptive in nature.

Data Description of Verity

We now outline the data sources that are available from Verity along with a brief description. Data sources are noted as “connected” if they are integrated and matched by account within the Customer Journey table.

Connected refers to when we can tie a contact or account’s firm interactions across different stages in the journey toward purchase. For example, we are able to tie together those that are exposed to our advertisements and those that came to our website. Another example is that we can see that a collection of contacts who visited our website (juniper.net data) converted into a sales opportunity (salesforce.com data). This is a form of contact to account connectivity. These integrated data are summarized as follows:

  • Customer Journey Table: This table combines important data elements that are extracted from the data sources below and linked (indicating how these data are merged) in this particular table (180 million records). The data are stored at the contact and account levels, enabling us to map customer-firm contacts by accounts to reveal the full journey.
  • Advertising data (connected): Using proprietary techniques, we collect an impression log of most of our advertising data.

  • Juniper.net data (connected): This is a complete file of all of the users that visit juniper.net. This file includes referral sources like SEO, SEM, campaign clicks, etc.
  • Marketing automation (connected): This dataset enables us to track events (Webinars, offline, Executive Briefing Center), marketing email activity, click2chat, 800call, and online form fills.
  • Salesforce.com (connected): All pipeline (sales interactions) data are included in this set of tables, including leads, opportunities, and closed deals. Closed deals are marked as won or lost.
  • SAP – include (connected): SAP is a financial management system that provides a view into sales achievement. Sales achievement is based on products that are sold and shipped or services that have been delivered.
  • Third-party data sources: We have incorporated buyer intent data from third parties. These are stored at an account level. The two primary data sources are:
    • Social: These data enable us to monitor feeds from sources like Twitter, LinkedIn, and Facebook. Additionally, they provide a competitive view of social media.
    • Third-party intent data: These data are provided by Bombora. “Intent” data signal buying interest from specific organizations based on topics we’ve created that are relevant to Juniper Networks.
  • Internal education data: The education data are integrated into Verity using an internal site called Juniper University and an integration with a training provider called Cornerstone.

Additional funds

Additional funds to support research efforts may be available from Juniper. These efforts may include opportunities to fund experiments, host researchers on site at Juniper Networks for an extended period of time, or purchase additional third party data. Please provide a brief description summarizing how these funds should be used. The selection of proposals will not be based on funding criterion. However, if the funding can enhance the research, then it should be outlined in the proposal.

Potential Juniper Data Lake Research Questions

Causal Attribution and Synergies for Marketing Touchpoints: Juniper Networks has prioritized each topic based on the level of interest from Juniper. Tier 1 is the highest priority and tier 3 is the lowest priority.

Attribution (tier 1)

Given the numerous, potentially synergistic marketing instruments, what is the relative effect of each in driving revenue?  Current approaches, such as path analysis, may not recover the causal effect accurately, raising concerns about interpretation of effect sizes. Further, purely experimental approaches do not scale to the desired level of granularity. There exists potential in combining experimental methods with models (e.g., structural approaches) to obtain cleaner measures of attribution.

Related, about 80% of Juniper’s business involves interactions with its partner firms, including resellers, consultants, and distributors. So a related topic of interest is the sales attribution problem across Juniper and its partners.

Synergies (tier 2)

How do the various marketing instruments work together or in substitution to drive sales (e.g., acquisition, cross-selling, up-selling, and retention)? For example, lead-generation from digital advertising can enhance salesforce productivity. Two immediate aspects worth investigating are (i) the determination of potential complementarities between marketing instruments and (ii) the determination of a potential sequence or pathway of optimal interventions.

New Marketing Variables (tier 2)

To date, information on data events, sales calls, training sessions, trade shows, and so forth have been limited, suggesting new potential insights into how each drives lead generation and sales.

Overtouching & Frequency Capping (tier 2)

What is the optimal timing of the various marketing touch points? There is also limited research and knowledge about the frequency and timing of individual marketing interventions as well as groups of such activities. For example, are three display ads and two emails within a day the same as two display ads and three emails?


Randomized controlled field experiments provide the most reliable data for determining the causal effect of marketing instruments. How should such experiments be designed (which variables, which channels, which customers, etc.), and how much replication is required to ascertain the attribution of causal effects? 

How can theory inform the design of experiments? To what extent do theories regarding the underlying mechanisms that drive the causal effect of a marketing instrument or synergies between instruments matter for designing experiments?

Experimental data also can be streamed into the data lake to provide more complete insights into marketing causals, and also to assess whether experimental effects are stable over time.

Heterogeneity (tier 1)

How do marketing effects vary across industries and customers?  What are the implications for targeting, customization, and revenue enhancement?

Granularity (tier 2)

A given account may comprise multiple decision-makers, such as the purchasing department, engineers and finance. How do the various individuals within the account drive the decisions of the account?  How do the effects of marketing vary across account members?

How should one aggregate information for decision making?  Suppose one determines that marketing spending in aggregate drives total sales. Total spending can be disaggregated by vehicle (e.g. promotion) which, in turn, can be further disaggregated by marketing tool (e.g. discount or e-mail).  Similarly, sales can be disaggregated by channel. In other words, what is the right lens for decision making – the effect of an email campaign on an account, or the effect of marketing spend on revenue, and how can the multiple levels of aggregation be integrated?

Sales Force Planning (tier 3)

How should one set sales force incentives?  Despite the long extant literature, there is considerable economic theory on the role of salesforce incentives and their potential unintended consequences. Moreover, the extant literature has not considered the co-existence of sales force and other marketing activities.

To what extent do sales outcomes reflect the effect of salesperson ability (adverse selection), salesperson effort (moral hazard), and/or other contemporaneous firm marketing efforts?

Does sales training affect sales outcomes, and what are the implications for sales compensation?

How do other marketing instruments interact with sales incentives?       

How should territory alignments and call plans be optimized?


Researchers are asked to submit a three to five page proposal outlining their research idea along with their CVs by February 16, 2018. Three to five proposals will be selected based on the scientific contribution of the research and the fit with Juniper’s priorities. The scientific contribution will be evaluated by a committee whose members include JP Dube (Chicago), Carl Mela (Duke), Sanjog Misra (Chicago), and representatives from MSI and Juniper Networks. Decisions will be communicated to selected teams by March 19, 2018.  After signing a confidentiality agreement that will allow for publication of research, teams will be flown to Juniper’s Santa Clara offices for a one to two day meeting to initiate the research projects.  Any completed research papers stemming from this research initiative are to be submitted for consideration in MSI’s working paper series.

Working papers play a key role in the dissemination of knowledge developed by MSI-associated researchers. These working papers are intended to provide new perspectives on perennial and future marketing challenges and to offer directions for further action and research.

Before submitting a working paper, please review MSI's Working Paper Guidelines and Terms and Conditions.

Also, if you have questions about submitting to MSI, please contact research@msi.org.

The pre-proposal title page should include the following:

  • Title: Title of Research
  • Researchers: Name, affiliation and contact information for all researchers

The pre-proposal main document should follow this format:

  • Abstract and Key Words: Max 500 word project description, and key words
  • Statement of Intended Contribution to Practice: A clear, concise statement of how the proposed research would provide a novel and interesting contribution to practice and what marketing managers might do differently as a result of the research findings.
  • Fit with MSI’s Research Priorities (if applicable): We especially encourage research pre-proposals that fit with MSI’s current Research Priorities (here) – we are also open to additional research topics that significantly advance marketing knowledge and practice.
  • Motivation and Research Question(s): A statement of the specific research question(s) that will be addressed, why they are important and interesting, and what the researchers expect to learn from answering these questions.
  • Brief Description of the Research Design and Methodology: Study design, data sources/collection procedures, experiments to be run (if applicable), modeling techniques to be used (if applicable), and any other relevant details.
  • Overall Funding and Support Needs: A brief description of the budget for the project including specific budget items and amounts (typically between $3,000 and $10,000).
  • Vita(e) of each of the researchers.

Pre-proposals should not exceed 1,200 words excluding vita(e) and title page.

Pre-proposals are encouraged to draw upon diverse theoretical perspectives and methodologies. Studies may be conceptual or empirical; and they may involve combinations of methodological approaches including literature reviews, comparative studies, observational and ethnographic studies, naturalistic, laboratory, or field experiments, econometric models, and so forth. Projects using multiple methodologies are especially welcomed. Researchers are encouraged to identify industry collaborators.

View MSI's 2016-2018 Research Priorities here!

Also, if you have questions about submitting to MSI, please contact research@msi.org.