Justin Trana

While it generally takes more time, look for ways to find joint go to market opportunities or ways you can partner through a third party to build a relationship. For example, co-sponsorship of an event or partnering as keynote speakers to build mutual brand awareness. If there is something in it for the partner they may be willing to foot the bill for early efforts while your work to demonstrate the value and build up a budget for future collaboration.

The hardest thing to do in this type of transition is to force the sales and marketing teams to pivot twice. What I would recommend focusing your energy on is how you can make the current process as stable as possible until you are ready to "flip the switch" on the overhauled version. Even if the current way of doing things is less than ideal, it is what the teams are familiar with and (hopefully) functions to some extent. Forcing a temporary change will likely slow down the lead gen and qualification process and have a negative impact on revenue. As far as technical areas of focus, lead routing automation is likely going to give you the biggest bang for the buck. Most organizations will put higher value on leads making it through the system faster to a point of sale than having perfect visibility into lead sources or attribution metrics.

The data on this type of dashboard is truly only as good as the input from the sales reps. The most effective way to get this data moving, with accuracy is to hold accountability via the sales leadership team. Opportunity stage progression measurement (aka "deal cycle time") should be a part of a quarterly forecasting motion. To hold sales reps accountable, leaders should work with their team to identify stuck deals that have the potential to make it into the quarter (or any time period) for closure. When the rep talks about a deal closing but the data doesn't match the narrative, the leader needs to push their rep to get into Salesforce and update the opportunity. To supplement this, you can put some visuals on your dashboard around number of deals in a given stage and average time spent. This will spark the "why" questions around how things can move faster and uncover the any data related issues.

Start with listening. The number 1 advocate and driver of a revenue strategy is the sales leadership team. Take the time to listen to this new sales leader and understand their underlying objectives while trying to keep the conversation agnostic of technology. Understand how they want to orient the team and where they want reps to focus. In my experience in this scenario, the most critical thing to do is NOT come with an agenda to pitch your plan with this new sales leader first. The majority of times, you are closer to the same objectives than you are apart even if you may not be speaking the same language yet.

Simple as it seems, I think what really matter is that you present what's in it for them first and foremost. The marketing team will have a very specific POV for what really matters to them, generally some form of attribution of up funnel activities to sales outcomes that helps them to measure ROI. Automation, especially lead routing, is a huge benefit to the Marketing team. Around the ownership factor, I find it best to create clear lines around pieces of the data or tooling architecture that each team should own. For example, the Marketing Ops team owns all data and routing tools as they related to Leads and lead routing, while the Sales Ops team owns everything related to Accounts and account data integrity. They are related so collaboration is key, but it's also very helpful to have clear lines when it comes to final decision making and support for troubleshooting.

Whatever makes the sales team more effective! The more you can focus on the tooling and infrastructure that keeps the sales team effective and focused on selling, not admin, the better. Your customer in building a revenue engine is the sales org and if they are losing patience while you build structure around back-office tooling you will lose their support for the future phases of work.

New logo lands and partner activity are great measures of long term success. I would also but renewal rates, average deal size, and length of contract terms (e.g. 1 vs 2 vs 5 year deals) as very strong indicators of the long term health of an organization that can easily be measured in the short term.

The best data dictionaries live in a system of record connected to the data source itself. Tools like Unity Catalog on Databricks or Alation surface the dictionary and governance on the same platform as the end query. This makes is more efficient for users as well as more transparent to keep updated. That being said, I have found it useful to start with a simple, collaborative tool like Google Sheets to get things started. Use this as your structure for a few months until the necessary information is curated and you align on the data elements that really matter. You can do your research on a more robust system at the same time as you generate version 1.