Whether customers engage with your brand on mobile, desktop, or social channels, they expect you to provide a synchronized, personalized experience.

For example, after a customer clicks on the banner ad you placed for kid’s shoes, watches your video on Facebook, and finally purchases on their phone, the customer doesn’t want to see an ad for those shoes at a discounted price.

Retargeting customers with the wrong message is the very kind of disconnect that every marketer strives to avoid. Even though the customer journey may stretch out over several days and multiple channels, your customers expect to be recognized and remembered.

The prevalence of consumer irritation with generic advertising is real and quantified. A survey found users want less ad frequency, more personalization, and relevant content across all channels. More specifically, the survey found that 78.6% of consumers will only use a brand’s coupons or other offers if they are directly tied to their previous brand interactions.

The ability to make real-time adjustments to the individual ads a prospect sees, tailored to match their behavior as they travel down an infinitely different number of digital pathways is precisely what customers are demanding from marketers.

We are using pixels to give us valuable and essential actionable data from site visits, digital ad impressions, email open rates, and sales conversions. But how can we process all of this data so that we can direct content to the right consumers at the right time?

We need to do more than just observe pixel data, but to proactively anticipate what prospects will find most useful at the precise time when they want it.

This is the key to delivering a personalized and efficient web experience to accelerate conversions.

AI Provides Clarity in Real Time

With its ability to synthesize large amounts of data points, artificial intelligence (AI) is processing insights in real-time and immediately putting that information to work to deliver hyper-personalized and optimized campaigns as they run.

According to Statista, AI is considered the second most effective digital marketing technique after content marketing.

In the marriage of pixels and AI, the benefit is how one leverages the data against what they are trying to achieve. AI’s deep learning capabilities can do more than simply observe pixel data but provide much-needed insights that allow BDMs to change, adjust and secure business outcomes.

The more data you have, the smarter AI becomes in creating campaign success. Let’s look at how this data is collected and how it can be used analytically.

As a key component of digital ad choreography, pixel tracking is at the core of orchestrating this type of deep intellectual engagement that consumers want.

As the name suggests, a pixel is an invisible 1×1 image inserted into your content that not only provides details about digital assets but also about the people viewing, opening, and engaging, including:

  •  Who the audience is (demographics, behaviors, interests and purchasing habits)
  •  Where they are coming from
  •  How they got there

What Are You Optimizing Against?

Pixel tracking done appropriately can lead to tremendous amounts of savings and efficiencies in overall campaign performance.

While most marketers know how to place a tracking pixel on their digital assets, many fail to understand the importance of optimizing behaviors based on the data.

Pixels can measure how consumers are engaging with digital assets, whether a visitor is “converting” into a customer, or whether the prospect takes action after learning about an offer or product.

Conversion tracking shows which platforms are working best for reaching and engaging customers with a high return on investment (ROI), and which ones should be abandoned.

If you want actionable insights from pixel data, you’ll need to ensure the data you’re collecting is being analyzed against the goals you’re looking to achieve.

Return on Investment (ROI) will not be positive if it’s measured against irrelevant actions. Purchasing may not always be defined as a conversion. With campaign goals and business objectives defined, optimizing against customer behavior can become more turnkey, whether that’s when a prospect:

  • Shares a piece of content
  • Opt-ins to an email list
  • Clicks a link in an email
  • Visits your website
  • Adds an item to the shopping cart
  • Begins the checkout process
  • Completes a purchase
  • Completes a review
  • Drives to a brick and mortar store

In being specific about what data you want to review from a placed pixel, you can see the level of performance of your assets, and where and when that performance is best generated in the consumer’s journey through the purchase funnel, and where that attribution of success can be awarded.

Attribution: Giving Credit Where Credit is Due

How far did the prospect go before they stopped and if they did convert, where can we attribute that conversion?

Attribution shows you how your targets are reacting, in real time, to each digital touchpoint of your messaging across desktop, mobile and social. Tracking the customer’s digital pathway lets you see the specific track they took before conversion to reveal which messages are delivering the highest ROI toward your specific campaign goals. This is critical for optimizing the program so that you can deliver intelligent retargeting.

For example, once the customer purchases the shoes, a burn pixel removes that customer from the list to prevent them from seeing repeat ads — especially ads that offer a discount.

You still have the option to retarget this customer with alternative cross-sell ads, but only if you have collected data about what your customers are doing before, during and after a conversion. You’ll also know which people have not yet converted so that you can continue targeting them with fresh messaging.

The key to driving this level of optimization is through pixel tracking that lets you know when to stop, when to retarget, and when a prospect still needs more data. The more data you can collect, the better. Combining pixel data tracking with CRM data, for example, can help you gather more accurate insights.

Focus on Personal Experience Rather than Awareness

The biggest hurdle with marketing attribution is collecting accurate insights. By combining AI with pixel tracking, BDMs can use real-time analytics to optimize their campaigns to deliver the right messaging, re-engage consumers, and provide intuitive retargeting. In a time when marketing dollars are limited, and consumers are increasingly tuning out marketing messages, it’s never been more important to use AI to drive conversions.

About the Author: Tiffany Coletti Kaiser is the EVP of Marketing at Digital Remedy. Digital Remedy is a digital media solutions company leading the tech enabled marketing space.