Integrating Offline Revenue into Analytics

Roy Hodges / 5th May 2017 / Comment

One simple question to start us off: what percentage of your sales is transacted offline with no correlation to online marketing activities?

Odds are, if you are a B2B company or even B2C, there are a portion of sales that may not be recorded in analytics platforms that were built to monitor the efficacy of digital marketing dollars. This information, omitted, may paint an incomplete picture or even miss opportunities for growth, success and even new markets. Attribution of marketing channels and revenue for all sales (online and offline) will do a better job and translate into better business decisions at the leadership level.

The effort to integrate offline revenue is not without its challenges. While challenging, with a good framework, commitment to success, the right engineers and quality control, you can unlock the benefit of bringing offline revenue from your ERP and CRM into Marketing Analytics systems to make good on the promise of Business Intelligence. Once complete, the next steps to actionable insights will be more reliable, more trustworthy and a key in determining the success against the competitive landscape.

The Steps to a Successful Offline Revenue Analytics Integration Project

  1. Architecture & Planning
  2. Engineering
  3. Quality Assurance
  4. Deployment
  5. Reporting & Analysis
  6. Maintenance & Support

1. Architecture & Planning

Before starting any integration project, it is important to get all the players and moving parts right.

  • What kind of ERP system is it? SAP, IBM AS/400, Oracle, Sage?
  • Is it a CRM system like Salesforce or Zoho?
  • Are there existing gateways to clone to save time or data feeds that can be leveraged?
  • What are the limitations of API calls?
  • Do we need to build a system for redundancy and reliability?
  • What offline revenue sources are there?
  • How do we store attribution information and what attribution model are we using?
  • How will we handle split-shipments, refunds and adjustments?

This is just a small list of the questions that need evaluation during the Architecture & Planning Phase. Wheelhouse’s Analytics and Engineering teams work together to put together a solution for passing revenue up to Google Analytics and other systems in an agile approach.

During the architecture phase, we recommend simultaneously planning for work by understanding costs, resource availability, skill sets, systems and future maintenance and support. Considering Project Management “Iron Triangle” during architecture and planning phases is key in ensuring reliable reporting, analysis and actionable insights are the successful fruits of our labor.

2. Engineering

When actually sitting down to engineer your integration there may be new skill sets required that some engineering teams may lack. OAuth, API, REST and other tools are used to communicate with Google Analytics and some engineering teams may not yet have the technical “muscle memory” to bang these out quickly. It is sometimes handy to have available engineering resources to help teams rapidly implement. During this phase, there will be engineering testing required to minimize lengthy QA cycle times. Wheelhouse has engineering on staff to help clients through this phase.

3. Quality Assurance

This phase is the final checkpoint to validate that revenue, attribution and transactions are all being recorded and adjusted as the ERP and CRM system moves customers through the sales cycle. This will require manual checking of data and most likely several rounds of Quality Control (QC) checks performed on behalf of vendors and the analytics teams to sign off that data looks good. Be sure to allow time for this phase, without it, the integration may jeopardize trust and result in failed integrations whereby a new vendor may be chosen to redesign, reverse engineer and execute. If there’s any place to find edge cases not found in Architecture, this is it, but with good planning and attention to what’s most valuable in the architecture phase, most of these edge cases are small and easily handled.

4. Deployment

With good architecture, planning, engineering and quality assurance processes, deployment should show little to no surprise and just offer delight in knowing that all the work to bring offline revenue into analytics pays off. Teams will usually be on standby to “smoke-test” a deployment for glaring issues, validate existing issues and finally triage and decide on fixing or shelving any unforeseen issues during deployment. Having a team that has forged bonds through the previous phases allows fast issue resolution and a sense of accomplishment to carry forward into future initiatives.

5. Reporting & Analysis

It doesn’t take long, and usually immediate satisfaction results as marketing teams start to gain insights on what marketing dollars are driving what revenue. Demographic models also can be used to further clarify new demographics in offline revenue that a company may have not gained insight too before. With multi-channel attribution models, the marketing team can dive deeper into what dollar counts where and deliver on the promise of BI.

6. Maintenance & Support

As we know in the Software Industry and Business, our job is never done, it continues forward. Systems change, websites change and analytics integrations will change. Have an upgrade to your ERP, or migrating to a new CRM system? With well thought out systems, attention to detail and adhering to the concept of Separation of Responsibility, change management and issue resolution should remain a small part of ensuring that data keeps flowing. As above, forging relationships through the earlier phases allows teams to forge trust and know that whatever happens, “we’ll handle it” and get marketing, sales and ultimately the business what they need for continued success.

Are you ready for Offline Revenue in your Analytics Systems?

Contact Wheelhouse DMG today for information about how we can help you connect your offline and online data so that your marketers can make better decisions. Wheelhouse’s Analytics and Engineering teams will work together to design and implement your solution.

By Roy Hodges