Cross-channel advertising is becoming a bit of an old news. However, not all marketers feel confident about how to apply it to achieve the best results for a brand. Countless options show up on the market on daily basis.
Today’s effective marketing tools become a matter of the past when new marketing technologies, case in point, artificial intelligence (AI), proliferate the market. It’s perfectly understandable to be confused.
If you don’t know where to start with your cross-channel marketing strategy, the safest way forward is learning more about the current place of the cross-channel customer experience in the martech industry.
Engagement, Experience, and Loyalty
Did you know that multichannel shoppers spend three times more than single-channel shoppers? With that in mind, and if you still haven’t done so, it’s time to put your customer first by adopting a cross channel marketing approach.
Once you understand its benefits and its challenges, it’s easier to overcome typical obstacles you may face when choosing a cross-channel marketing platform. Arguments like no time, no money, and no approval by the higher-ups need to be reconsidered in view of the personalized, consolidated, time-resistant marketing results packed in a seamless customer experience. That’s something customers expect from brands, at least 87 percent of them, which is a number not to be messed with.
By drawing data from multiple channels, you’ll use multiple touch points to deliver your brand message, and be able to better communicate with customers.
Crossing the Line Between Online and Offline Customer Experience
Although marketers are used to speaking about customers as a part of the martech industry, it’s important to grasp that it surpasses the digital space. As the line between online and offline customer behavior gets thinner, cross-channel marketing software can help you familiarize with your customers in-store and in the ecommerce world.
Simply put, cross-channel advertising is about the single customer view (SCV). The single customer view is the single record of all data concerning your customer, including browsing histories and shopping habits, the demographic profile, website, email and social media interaction, and information from the brick and mortar stores.
Finally, cross-channel advertising is about consolidated and personalized communication, which follows the customer journey during the customer lifecycle, playing an active role in customer engagement and experience, all the way to nurturing a loyal returning customer.
Personalization Challenges: Too Much Data, Too Many Tools, and Brand New Customers
Achieving perfect cross-channel advertising results is challenged by the huge volume of longitudinal data produced by tracking customer behavior during the customer lifecycle, across channels, and over time. All data collected from email campaigns, in-store behavior, and demographics need to be consolidated in one place, in a presentable view, and regularly updated so that the generated reports reflect the reality of the individual customer experience.
It is often impossible to have a single advertising tool with enough power to help marketers process all data at once. In fact, marketers have over 5,000 tools to choose from – no wonder many of them end up using at least a dozen on daily basis. That’s a whole load of data to process, and it can seriously affect the campaign success, especially if it requires a lot of manual work on behalf of the marketer.
Brand new customers are a different challenge. Typically, there is not enough data to understand where they come from. Cross-channel advertising metrics can be tricky to measure, but with the right tools, you have greater chances of obtaining decently precise insights and using them for your business benefit.
The Shift Toward AI Marketing
Applying artificial intelligence across all touchpoints of the customer journey can substantially change:
- How well you know your customers
- How much time you spend on developing targeted campaigns, and
- How efficient you are in applying the analytics insights.
For now, AI in marketing is in its spring. Although not every marketing team has adopted machine learning marketing to automate repetitive processes, test campaigns, analyze data and design campaigns, if we are to consider industry trends and predictions, it will soon be inevitable to lean on AI marketing tools to effectively connect with customers.
AI Marketing in Theory
Artificial intelligence helps machines (computers) become smarter by applying a range of AI techniques, such as machine learning, deep learning, natural language processing and neural networks.
AI in cross-channel advertising is about creating an intelligent blueprint of the processed and analyzed data, which is collected in the digital and the physical world, and about injecting it into a cross-channel marketing platform.
Such platforms possess smart capabilities of learning, data processing, and analytical reporting. In a way, they replicate the human brain, at the same time being more effective to do the same with less effort thanks to the ability to work with more data in shorter time periods and in new ways.
AI Cross Channel Marketing in Practice
Practically speaking, AI marketing can be applied to multiple messaging channels and help marketers enhance results in:
- Smart content creation. Smart content is content that is measurable, easy to be found by the right customer, optimized once it’s generated, and organized well enough to match the related topic.
- Voice search. By using natural sounding language for voice search instead of shorter search phrases, customers have greater chances of reaching the right brand.
- Programmatic media buying. Programmatic ads target the right customer, in the right context, by real-time bidding for the available advertising inventory.
- Propensity modeling. AI marketing tools improve the chances to develop better propensity models by extracting data about customers with rich buying histories – those that have the greatest buying affinity.
- Predictive analysis. Making accurate predictions for future events, such as the likelihood of hitting the purchase button, by whom, when and how, is easier with AI marketing that predicts with more precision on the basis on learning from past historical and transactional data.
- Lead scoring. AI contributes to improved lead scores and polishes the conversion rate assessment by prioritizing customers and aligning them with sales messages.
- Ad targeting. Target the most receptive audience with sophisticated machine learning models that use customer’s behavioral and psychographic data from shopping and browsing habits.
- Dynamic pricing. Determine the best pricing model for your product or service which is aligned with the customer’s perceived ability to pay.
- Re-targeting. Improve low starting conversion rates by better analyzing data dissipated in the crevices of multiple marketing channels and lost over time.
- Marketing automation. AI marketing finds the shortest possible route to complete a process, automating many of the manual processes that compete for the marketer’s time and attention.
If you want to improve your conversion rates by implementing artificial intelligence tools into your cross-channel marketing campaign, it’s time to let Frank help you!