Digital marketers have a ton of data at their fingertips. So much data, in fact, that sometimes we don’t pause to ask ourselves, "What valuable data could we be missing?" More specifically, "What data do our clients have at their disposal, and how could we use it?"
In another post, we outlined 5 Questions Digital Marketing Agencies Can Ask Their Clients to Become Better Partners. These types of questions are important, because engaging in meaningful conversations with clients allows us to find ways to leverage the business data they have at their disposal. This is what really takes a digital marketing strategy to the next level. Why? Because their business data translates directly to their bottom line, and when we can find ways to use it, so can our campaigns.
To elaborate on this point, here are three real life examples of ways our paid digital marketing team has used internal business data to measure campaign performance, make smarter campaign optimizations, and set impactful goals.
1. Tracking Customer Lifetime Value
We have worked with an ecommerce retailer for many years, managing Google Search and Shopping ads for around 20,000 products. With this particular client, our key performance indicator metrics are return on ad spend (ROAS) and revenue. Results were consistently stellar with both investment and ROAS increasing over time. We monitored these metrics at a campaign and even product level and felt like we had a really good grasp on performance so we challenged ourselves by asking, “How can we take this one step further?”
During a conversation with the client, our contact mentioned that they were curious about how the lifetime value of their customers varied according to the advertising source or campaign that brought them in. They wanted to answer questions like:
- “Is paid search bringing in one-time shoppers, or loyal repeat customers when compared to other channels?”
- “Are the people we are reaching in Campaign A as valuable in the long term as the people we are reaching in Campaign B?”
To answer these questions, we worked with the client’s development team to apply tracking parameters to our ads so that they could pull information on the campaign and source associated with each customer into their internal CRM system.
Having this data within their CRM allows us to collectively determine which campaigns are bringing in repeat shoppers, and which are bringing in customers with lower lifetime values. We use this information to identify top performing campaigns and inform budget, bidding, and campaign optimizations decisions.
2. Tracking Leads Through To Converted Customers
A client in the financial technology space was having an issue with fraudulent lead submissions. From our perspective, things were going really well for their account. They were running ads on Google Search and their key performance metrics of lead volume and cost per lead were heading in the right direction over time. However, when we met to discuss these results, our conversation led us to discover that the lift was not being realized on the business’ bottom line. Despite rises in lead volume, new customers were trending downward as an increasing number of leads were not making it through the approval process. This is when we realized that we had an apparent issue with lead quality, so we put our heads together to figure out how to combat it.
The best weapon we had against faltering lead quality was finding greater transparency by way of lead qualification. In order to optimize for high quality leads, we needed to take lead quality into consideration when making account decisions. For this client, using a custom lead qualification form to track users from the moment they become a lead, to the moment they become a customer, was a necessary next step in meaningful campaign refinement. We needed to track lead quality over time to have an understanding of which leads were being rejected, and which ones were turning into valuable customers.
We again relied on our knowledge of tracking parameters and worked with the client’s development team to start recording information on the campaign and source that drove each lead within the client’s CRM. Doing this allowed the client to track and report back on the number of approved, rejected, and won accounts that were driven by our paid search ads each month. We were no longer solely gauging our campaign performance on lead volume; we could now tie it to actual customers and revenue!
Doing this opened the door to a world of possibilities and advanced optimization strategies. Here are a few of the ways we have used this internal business data to gauge performance and drive improvements in our Google Ads campaigns:
- We track and report on lead quality, or for this client, “approval status”. We celebrate when approved accounts trend up and rejected accounts trend down.
- We adjust bidding targets based on historic lead quality at the keyword and ad group levels.
- We upload approved accounts as offline conversion actions. The AI-driven smart bidding technology uses this signal to target users who are likely to become qualified leads.
- We examine lead quality across various ad copy in order to cater our messaging to avoid product confusion and poor-quality leads.
- We pause keywords that lead to rejected accounts and expand on keywords that bring in approved accounts.
3. Setting Budgets & KPIs Based on Close Rates
A client in the real estate industry tasked us with recommending digital marketing budgets and key performance indicator (KPI) targets that would be large enough to support their community sales goals. The KPI metrics in use for this account are lead volume and cost per lead. Throughout the sales process, the website leads typically convert to physical foot traffic by way of a home tour prior to purchasing.
To inform budget and KPI recommendations, we asked the client to provide us with all of their internal figures on last year’s online lead, walk-in, and home sales volume. They had already used this information internally to set foot traffic goals for each of their communities. We planned to use it similarly on our end to set lead goals for each community, and then to use our historic cost per lead data to back-out into recommended budgets.
By pairing the client’s internal sales data with the lead data seen on our end, we were able to determine estimated close rates for their business. These close rates were further broken down to lead-to-walk-in rate, and finally walk-in-to-sale rate, matching their sales process. Once we determined these close rates, we were able to make a couple of key recommendations to help our client reach their sales goals, including:
- The number of leads needed to reach internal foot traffic goals, and ultimately, sales goals.
- The amount of budget needed to achieve internal sales goals.
- This was determined by applying the historic cost per lead to the calculated close rate, and taking into account the percentage of leads driven by each channel.
Making Smarter Optimizations Using Internal Business Data
In order to perform our due diligence as marketers, we must continuously challenge ourselves to consider what business data we may be missing or underutilizing. This process starts as a simple conversation. If you’re thinking about how to take your business's digital marketing to the next level, we’d love to chat. Reach out to our team today.