It used to be that if you had a brick-and-mortar shop, you could simply ask how a customer found their way to your shop. They might mention an ad they saw on TV, show you a flyer distributed at a community gathering, or tell you a friend recommended them. With online sales, tracking what prompted a customer to visit your site is much trickier.
Selling online is a double-edged sword. Essentially, the same element that makes it easier to cast a wider net can create other issues, leaving marketers lost in a sea of results with little idea of how they got those results. Tapping into a variety of different advertising avenues to pitch to potential customers — Facebook, Google, email, Instagram, Tik Tok — is no doubt a boon. However, if you are unable to harness information about what actions your customers take once they reach your site, it can make it difficult to maximize your campaigns.
Salesforce has anticipated this with its Datorama suite. Datorama (currently known as MC Intelligence) can help your business tease out meaningful information from your ad campaigns, empowering you to better measure performance so that you can more effectively target customers.
Datorama follows the thread of a sale back to its source and aggregates that data for you. We call this attributing a sale back to its origin. After a customer sees an ad, and if they click the ad, Google will track their activity with a cookie. Your website can then pass the cookie data to your CRM or ERP system with what action a customer took. Understanding the initial data point — that a customer clicked an ad — doesn’t truly tell you how that ad influenced the customer.
By just tracking clicks, you have no idea of the return you’re getting compared to how much you spent on the ad. Clicks are not a concrete enough measure for campaign performance. Likewise, if you just looked at aggregate sales, you wouldn’t have a good idea of what generated that sale. Maybe the campaign was running at the same time as the sale, but then again, it could have been good old fashioned word-of-mouth. Taking data post-click and funneling into a sales bucket allows you to make sense of customer motivations and get a handle on the catalyst of a sale.
If, say, the ad prompted a customer to visit your site and purchase $2,000 worth of tchotchkes, just knowing that they clicked the ad will not give you insight into how much they spent. It doesn’t give your marketing team a holistic understanding of the customer’s journey. Every customer who sees your ad may visit your site, but maybe the interface is not intuitive, so nobody buys anything. So, while the ad successfully drives customers to your website, the website is the weak link in the chain, which leads to poor sales. In this case, the ad is actually a huge failure.
This is why campaign attribution is important. Campaign attribution allows you to, for instance, see that your New Year’s sale cost you $5,000 and generated $15,000 worth of sales — important information to have when determining how to best use the money you spend on ads.
Attribution can grow in complexity, such as tracking first touch. Let’s say a customer first hears of your company from an ad and fills out a contact form but doesn’t purchase anything. Then, several months later, they return to buy something. With this attribution method, you know to file that customer under the umbrella of the ad campaign that initiated that first touch, no matter how long between that first touch and the last touch. This gives you insight into the lifetime value of a customer.
If a campaign takes longer between first touch and last touch, for instance, with attribution you understand that its power is in getting customers interested in your brand. So, that campaign is something you should run to bring in new customers not, to say, incentivize existing customers to buy more.
Similarly, using last touch attribution can highlight what caused a customer to finally pull the trigger on making a purchase. Both tactics are very useful, but knowing how to delineate between the meaning of one versus the other is only possible if you know the genesis of the customer journey — the barriers that prevent them from purchasing, what prompts them to buy and so on. Fundamentally, attribution allows you to get inside your customer’s head, understanding what drives their interactions with your company.
By having Datorama, you are also able to assign weights to different methods of customer acquisition. If you called a customer, sent them an email and showed them an ad, you are able to assign a percent for each touchpoint, establishing concretely how each method contributed to a sale. Adding another layer of sophistication, you would even be able to assign a degrading effect so that newer touchpoints count more.
Whether you’re a B2B or B2C business will govern what links in the chain matter more. B2B companies typically care more about first touch since they are more long-term focused, emphasizing getting new customers. Getting a handle on what initially inspired a customer to make contact is more important for B2B companies.
On the flip side, B2C companies often care more about the last touch. They often want to see what happened right before a customer made a purchase, because, most likely, that is what prompted the customer to make the purchase. Obviously, if a company is big enough, they might adopt a hybrid model, striving to understand both first and last touch.
One of the biggest benefits of Dataorama is that it offers a unified data model. Your company has campaigns (e.g., your winter sale), media buys (e.g., that ad on the banner of the Wall Street Journal), and creative (e.g., showing different content specific to a given customer). With Datorama, when you bring in data from Bing, Facebook or Google, it all fits into a single model. This allows you to report, across the board, on all three. Once you have that data, Datorama has a wealth of harmonization tools that allow you to see how the data ties back to each campaign, unifying the structure and naming conventions that differ between each platform.
While an experienced partner is not an ad agency, they can help better understand marketing data. They can work with companies to retrieve the urchin tracking module (UTM) tag from the platform, get it pushed over to a website then to Salesforce. When working with a partner, it is important to understand their naming structures and having a consistent view across ad data sources.
A partner also needs to understand what level of harmonization your company needs. If you have conflicting data streams, understanding which one takes precedent is key. Once your data is set up, a savvy partner will allow you to visualize that data with Insight Bots that give you different AI metrics for various key performance indicators (KPIs), for instance telling you why your conversion rate is high or low for a given month.
Knowing what connections you want to make and what KPIs you want will help your partner know how to approach setting up your data. The number of leads generated per ad or the cost per lead are good examples of this type of insight. Because it is narrowly focused on marketing, Datorama is not an end-all-be-all solution for all companies reporting needs, but it will greatly improve your company’s understanding of its customers’ interactions with your marketing. So, instead of tracking clicks, track the entire lifecycle of a customer.