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You can finally Get the whole story™.
Not just which ad they click on, but the websites they visit, the searches they conduct along their path to purchase, and more.
Where they’re showing up, what’s driving their traffic, the content and ads they use, and how you compare.
So you know how to get more out of every asset, from blogs to media spend.
Only DemandJump enables you to do all three.
Making the right marketing decisions with intelligence and confidence is more important now than ever before. You need to know how to measure the results of your marketing campaigns and identify which campaigns are driving revenue. These data-driven insights give you a greater understanding of where you should spend your marketing dollars to optimize your spend and return on investment (ROI). The most effective weapon in answering these questions is to accurately measure campaign performance.
Right now marketers have more data and tools than they know what to do with, but they’re still not getting the insights they need to reach their target customer at precisely the right moment when it matters most. DemandJump takes the guesswork out of digital marketing and removes blind spots by revealing more of the Customer Journey and Competitive Landscape than ever before.
With product features like Consumer Insights, Market Intelligence, Cross-Channel Analytics, Marketing Attribution, and Channel Optimization Recommendations, the DemandJump platform allows you to:
The most innovative marketers are using something called campaign influence to measure what works and what doesn’t. By measuring the results of a marketing campaign and campaign conversions, this helps marketers make better decisions with future campaigns. Using campaign influence is a strategy that not only reveals which marketing campaigns lead to closed won revenue, it also reveals exactly where in the customer journey those touchpoints are most effective.
A critical aspect of developing an effective marketing strategy is knowing which campaigns are driving the best return on investment (ROI). Armed with more insightful data means you can allocate resources more effectively to acquire new customers and plan for future growth. Yet despite this, many companies fly blind by not properly assigning credit to all the touchpoints along the customer journey.
Savvy marketers use campaign attribution to measure campaign influence as it relates to the customer’s journey. Campaign attribution demonstrates how campaigns generated revenue by influencing prospects to buy. This means measuring benchmarks by taking a deep dive into the intricacies of campaign influence by asking questions that matter to the campaign.
Cross-channel marketing campaigns come down to engaging with your target audience across multiple digital channels and devices. Today’s consumer moves seamlessly from their inbox to social networks, then to the web, using multiple devices such as PCs, laptops, tablets, and smartphones. They fully expect marketers to meet them wherever they are on their journey. They also expect marketing messages to be personalized and relevant to their tastes and preferences. They want the engagement to be easy to understand, use, and allow them to navigate seamlessly to what interests them most using their preferred device.
Cross-channel marketing campaigns allow marketers to employ multiple marketing channels such as:
Cross-channel advertising and retargeting campaigns are often more effective because campaign conversions rarely happen on the first-touchpoint. Marketing across multiple channels provides more opportunities to convert a consumer on their path to purchase. This added complexity makes it difficult for marketers to provide an engaging and seamless experience for the consumer.
It’s even more difficult to track and monitor the actions and movements of your target audience and use campaign attribution modeling to reveal insights into which efforts carry more conversion influence. It’s also difficult to ascertain exactly when in the customer journey those efforts are most effective. This is where it is helpful to take advantage of multiple attribution models. Some models are better equipped for campaign attribution than others, so now we will dive deeper into those different models.
Marketing attribution models assign credit for conversions or revenue to marketing campaigns. This person-centric approach is why attribution models are more typically applied to digital campaigns than those conducted offline, such as print advertising.
The most effective attribution models will provide insight into:
To find answers to those important questions, marketers need to embrace multi-touch attribution marketing models to effectively manage, optimize, and scale campaign performance. But, what if you don’t know which attribution model is best for your business? The wrong attribution model could assign credit to only one channel when the consumer had multiple touchpoints, possibly leading you to ignore other higher-performing channels.
Before picking a marketing attribution model, it is smart to consider the industry in which you work. Each industry has differing sales cycles, so it is important to pick a marketing attribution model that aligns with the consumer purchasing journey most common in your market and industry. Oftentimes it is best practice to use multiple attribution models to get a comprehensive look at how each of your channels influences conversions.
Although there are dozens of possible attribution models, they can generally be narrowed down into three categories.
1. Single-Touch (e.g. first/lead-creation touch, last/opportunity-conversion touch)
2. Multi-Touch Attribution (e.g. W-Shaped or Linear)
3. Full-Path (which includes post opportunity stage marketing)
The Single-Touch Attribution Model gives 100% of the credit to a single marketing touchpoint. The single touchpoint is often the first or last one engaged with by the consumer. The First-Touch model overemphasizes the top-of-the-funnel marketing channels that drive awareness. For this reason, single-touch attribution models are less widely used today, as they fail to provide a nuanced look at the complete customer journey.
Another example of Single-Touch Attribution is the last-click model, which attributes a conversion to the last marketing touchpoint, the touchpoint that directly results in a conversion. However, this approach neglects to consider the entire customer journey. First-touch attribution assumes the consumer chose to convert after the first advertisement they encountered, therefore, giving full attribution to this first touchpoint, regardless of any additional messaging they may have seen subsequently.
Each of these methods fails to factor in the entire customer journey, therefore marketers should avoid relying solely on these attribution methods. Last-touch undervalues any awareness channels like blog posts, social media, or advertising all important in the marketing mix. These channels play a huge part in building your brand and are a valuable component of any marketing strategy. While Single-Touch Attribution models often don’t tell the full story, they still have value when used alongside a multi touch model.
It is widely believed that it takes 6 to 8 touchpoints to generate a viable sales lead. Multi-touch attribution models look at all touchpoints engaged with by the consumer leading up to a purchase. As a result, these are considered more comprehensive and depending on which multi-touch model you use, they might assign value to channels differently.
For example, some assign value based on when a consumer interacted with a touchpoint relative to the conversion, while others weigh all touchpoints equally. These models are largely differentiated by how they divide credit between touchpoints on the path to purchase.
Full-Path Attribution models, also known as Z-Shape models, give you insight into all touchpoints throughout the customer journey. This model is also known as a position based model because it attributes different percentages of the conversion to each touchpoint based on where it fell in the path to purchase.
In designing your campaign, be mindful of these common campaign attribution errors and factors that influence attribution.
Advertising with Google Ads starts with creating a campaign based on your advertising goals. For example, if you'd like to show ads on Google.com to get more visitors to your website, you should choose a Search Network campaign. Each advertising network has different types of campaigns to choose from that should be aligned with your goals. You can select a goal for your campaign based on the actions you’d like your customers to take such as download a free ebook, click on the advertisement, call you, or visit your website as an example.
You can also select a campaign type, such as Search Network, Display Network, Shopping, or Video. You’ll then see recommendations within the app for features and settings that will help you meet your campaign's main advertising objective. Keep in mind that all campaign settings and features will be available to you despite what goal you choose, and you can always make a change to your goal, or choose not to use a goal.
Goals could include:
Choosing a specific campaign type determines where customers will be able to see your ads, but you make this more specific by targeting your ads.
Campaign types include:
Google Ads mistakes can derail your data collection strategy and become very costly to get the outcomes you want. Here are four of the most common attribution mistakes when using Google Analytics:
Some mistakes are so common, like those above, that nearly all sites will make them. Some can be quickly remedied while other mistakes are quite a bit sneakier, and you may not notice them until it’s too late.
It’s important not to trust your data blindly. You should be continually asking questions that challenge your assumptions.
Time is money we know, but not spending enough time on your overarching marketing strategy can lead to costly mistakes. While trying to get things done, it’s important for someone to challenge the strategy with questions, “ Are we aligned with consumer behavior?” or “ Are we answering the right questions?”
Diving in too quickly when setting up Google Ads can backfire on you if you rush into a campaign too quickly without much forethought. Google Ads mistakes are usually macro-level details dealing with how you approached tracking and analysis in the first place. Conquering this aspect before placing Google Ads means your attitude, knowledge, and approach will naturally fall into place.
Wherever you can, automate reports within Google Ads to eliminate human error. Anytime you are completing a task manually that can be automated, you are wasting precious resources and leaving yourself open to error.
There’s simply no reason to hard code Google Analytics onto your site. Google Tag Manager is free, and you can use it to organize your tags, including Google Analytics. Installing Google Analytics using Google Tag Manager will open up further opportunities for advanced tracking down the line as well.
Remain open to change throughout the entire lifecycle of any marketing campaign as the modeling you are using today may need to be adjusted as campaigns evolve in the future.
Be confident that you're making the best marketing decisions for your business. Request your 30-day free trial of the DemandJump platform today to understand more about how to optimize your marketing spend using automated attribution modeling.
Consumer Insights and Analytics
Competitor Analysis Tools
Customer Insight Research Techniques
Customer Journey Map
Marketing Analytics Techniques
Opportunities of Internet Marketing
Types of Consumer Insights