Posted inAnalytics / Content Marketing / Strategy

Combined Marketing and Sales Data Delivers Better ROI and Customer Journey Analysis

Article Highlights:

Bringing together marketing and sales metrics can be a challenge, especially for B2B organizations. But unifying marketing and sales data optimizes their efforts and creates better customer experiences. In this article you’ll learn: 

  • B2B challenges to the customer journey and campaign ROI
  • How marketing and sales can align for better insights 
  • Optimizing campaigns for more efficient outcomes

Data is the ultimate unifier for marketing and sales teams. By having a shared understanding of not only customer interactions across all touchpoints, but also the impact they are having, marketing and sales teams can better align on and accelerate their common goals. And when that happens, everyone wins. 

While it sounds straightforward enough, bringing the data metrics from these two teams together can be a challenge, especially for B2B organizations.

Think about the typical B2B marketing and sales workflow. The B2B marketer has a web analytics tool like Adobe Analytics or Google Analytics in place. This tool helps them track all their marketing campaigns, both inbound and outbound, by tracking where people are coming from, which pages they are visiting, how long they’re staying, what they’re consuming on the site, and where they go and what they do next. B2B marketers also use a variety of tactics like SEO, SEM, and social to find customers and direct them to their site. And of course a marketing automation platform (MAP) plays a role in engagement campaigns to qualify leads for sales.

Data, though, doesn’t end with the marketing team. The sales team has its own tools and metrics to track and analyze its outreach efforts. At the same time sales is interacting with a lead, though, that lead is also still interacting with your brand online, yet that’s being captured upstream by marketing, not sales.

The disconnect of tracking these different marketing and sales activities in separate locations, but for the same customers, can leave you with a flawed ROI analysis, holes in your customer journey, and generic, disjointed customer experiences.

A makeshift solution for campaign ROI

In short, B2B marketing and sales teams rarely have combined analytics on customer activity from the first touch all the way through to closed deals and beyond. To make up for this deficit, especially when calculating ROI, some groups focus on conversions that happen higher in the funnel.

B2B customers aren’t jumping online, viewing an ad, reading a review or two, then buying a pair of $100 sneakers. Instead, they’re spending several months researching, reading, and conferring over the right million-dollar SaaS investment — and marketers can’t always wait that long to report the results of quarterly campaigns.

However, opportunities often open within the first few weeks of an ad or marketing campaign, if not immediately. Using that data, you could calculate cost per SQL versus more traditional metrics like cost per click (CPC), which aren’t as discerning. But you’re still not at a true ROI that helps you understand the total cost of a sale.

Making the connection: Passing campaign data to your CRM

A higher level of analysis — understanding the influence of top-of-funnel content on bottom-of-funnel conversions — can only happen if you’re associating data from initial lead-generating activities at the top of the funnel straight through to your CRM activity and all the way to closed deals.

Many enterprises take the basic approach of passing marketing campaign data into their CRM along with the qualified leads that campaign generates. You may also track certain touchpoints within your MAP. Let’s say, for example, you run a lead gen campaign where you offer a downloadable white paper in exchange for customer contact information. Along with leads, you pass into your CRM as many attributes of the marketing campaign as possible, including fields for data on the channel, campaign, ad group, ad, etc.

With that information in your CRM, you’ll immediately know you have a lead that came from LinkedIn or search or your latest digital marketing campaign — and that’s better than nothing from an attribution perspective (though it will only be the last touch).

Being able to accept this data in your CRM, though, requires either a strong sales ops team — and a good relationship with that team — or marketing access to create custom fields in the CRM so this data has a place to live. With this information, though, you now can follow that individual customer throughout the rest of their journey in your CRM and tie any sales back to a specific marketing campaign.

However, if there were a way to see all the campaigns and content that influence your customers, you could map their entire journey to the current moment, leading to more relevant and timely outreach from your sales reps.

Taking it to the next level: Bring CRM data into your marketing analytics dashboard

Instead of tracking campaign data in your CRM, think about the benefits of bringing your lead and customer information into your web analytics platform.

Your analytics solution is designed to help you derive insights about how your actions and your customers’ actions are affecting revenue. While this is easily doable for B2C ecommerce, offline B2B conversions are not readily available unless you have a way to integrate that information with your marketing analytics and can match CRM customer records with visitor IDs.

But once you stitch CRM lead IDs with visitor IDs in your analytics solution, you’ll be able to illuminate the full details of the customer journey on a very granular level — inside of your analytics platform.

Again, many marketers focus on a small piece of the journey — usually the last page a prospect looked at before becoming a lead. And similarly, sales teams focus on their interactions with customers once they are in the pipeline. But as a content marketer you may be interested in understanding the full influence of what you publish — from discovery through to closed deals.

Once you stitch CRM data with analytics data at the visitor-level, you’ll see every single piece of cross-channel content a lead engaged with before they were in your sales pipeline, as well as after they were passed to sales.

The flow of information looks like this:

  1. First, a web analytics visitor ID is passed into your CRM client. 
  1. Next, you can stitch together the entire history of web touches for each opportunity contact in your CRM — provided they have this web history. 
  1. This connection enables you to tie revenue and sales opportunities to individual campaigns, pieces of content, and any marketing initiatives while helping marketers learn which campaigns and programs have the biggest impact on revenue — not just conversions.
  1. Then you can view important CRM information directly in your analytics program and gain insights on which content best nurtures leads to become loyal customers. 

Getting a picture of the complete customer journey, once analytics data and CRM data are stitched together, helps you make the best decisions about how to optimize your marketing campaigns. And anyone from C-Suite decision-makers to marketing and sales managers, data analysts, content managers, and more can easily access the insights you’re working with.

Use your data to continually optimize

Once this end-to-end data is in place, the next step is to put benchmarks in place — for example, that cost per MQL or cost per SQL. Set those figures then work to beat them with each campaign. You can also identify how many touches it takes to close a deal. The more you can lower those costs with data insights, the more efficient your campaigns will be.

That’s powerful. Where we were all once flying blind, now we can clearly see what it costs to create open B2B opportunities and, with that, identify ways to improve at every level.

Contact Stoke for more about how our proprietary performance analytics solutions can help you optimize every campaign. Learn more about the Adobe Analytics + Salesforce Integration and the Adobe Analytics + Microsoft Dynamics Integration.