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6 Challenges of Omnichannel Marketing Automation and How to Overcome Them

Customers convert faster when they get real-time personalized experience at any touchpoint of their journey. Learn why omnichannel marketing is a critical strategy in this new reality.

Maria Dorogokupets
Digital Enterprise Researcher
Updated: May 26, 2022
Published: July 26, 2019
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A customer journey used to be a single trip to the store. Now customers toggle between multiple means of reaching out to a business: calling, writing an email, visiting a site via mobile or desktop, connecting on social media, or driving to a brick-and-mortar store.

What’s more, they expect brands to provide tailored experience at each touchpoint of their journey. Consequently, to stay competitive and increase customer retention rates, businesses should not only be present on those channels. They should be omnipresent. Here is where an omnichannel marketing strategy comes in handy. 

What is Omnichannel Marketing?

what is omnichannel marketing

Businesses that focus on an omnichannel approach face two conflicting tendencies:

  • Multiple channels make people spend more thus opening new opportunities for revenue generation.
  • Customer journey mapping gets increasingly complicated.

Recent stats reflect this state of things:

importance of omnichannel marketing

To bridge this gap, a number of tech solutions emerged to help with handling marketing automation across multiple channels. Here’s the catch, though. According to the same Brightpearl research, 74% of respondents aren’t satisfied with their omnichannel marketing solutions. Technology that is here to help also comes as a barrier: only 12% of retailers have managed to implement technologies to support their strategy. Why so?

Similar to many situations in our life, omnichannel marketing automation has fallen victim to the “expectation vs reality” mismatch. 

87% of retail leaders perceive omnichannel marketing as critical or highly important to success.
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How Technologies Help to Manage Omnichannel Marketing Campaigns

To cover the “expectation” side, we’re looking at the ideal workflow where marketing technology magic helps to automate complex processes and improve customer experience:

how technologies help to manage omnichannel marketing

Data Unification

Customers constantly move between channels and devices. They can even use a few channels simultaneously. In order to get a complete picture and ensure cohesive experience across all the channels, businesses need to integrate data from their data sources, be it CRM, competitor intelligence, PPC campaigns, or social media.

common technologies for customer identity

A single platform with integrated data sources comes as the most obvious solution. Salesforce, for example, will store clean data from all the sources that can be further used to manage customers’ touchpoints and discover ways to personalize them. 

Customer Segmentation

Businesses need to understand who their target audiences are and further segment them based on their actions to provide personalized experience. An AI-powered platform, like Salesforce Einstein, can bear the burden of this highly complicated task. It will pick up trends in customers’ behavior, like average time spent interacting with a particular marketing asset before conversion, or specific campaigns with high conversion rates. Such powerful intelligence tools make it much easier to segment customers, prioritize channels, and serve the best personalized experience a business can master. 

Experience Personalization

Customers expect companies to cover their needs whatever channel they are at. That’s why marketing efforts are gravitating toward the contextual awareness about where, when, and how customers interact with brands. While unified data is the foundation for personalization, AI technologies actually make it happen.

For example, AI platforms can serve dynamic content based on the history of customer engagement: recommendations of related products on the basis of previous searches, push notifications based on a particular action on the site, or emails based on a particular purchase.

marketers experiment with AI

Performance Measurement

Marketing campaign performance needs to be measured from different perspectives. When a lead is generated or a deal is closed, it’s important to understand which decisions have most impact and which departments should be credited for it. A central analytics hub integrating all the employed data sources is the solution to tracking impact of different teams’ efforts.

A single platform for integrating data sources, like @salesforce, comes as the most obvious solution to customer data unification challenge.
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The Challenges Hampering Omnichannel Marketing Automation—and Their Solutions

While the use of dedicated data management tools is obvious for making omnichannel marketing possible, many businesses find it difficult to apply them properly and drive any tangible results. Let’s look at the challenges impeding omnichannel marketing automation and the ways to overcome them to provide cohesive customer experience across all channels.

Challenge #1. Absence of Data-Driven Corporate Mentality

Omnichannel marketing automation relies on large data volumes. However, without data-centric corporate mechanisms, businesses cannot leverage this firehose of data to personalize customer experience across multiple channels. 

The Solution

Data-driven mentality requires:

  • A central data management hub that unites all the data sources available. All teams that participate in marketing campaigns should have access to this hub. What’s more, they should have an idea of what kind of data is available.
  • A data dictionary where all the metrics are explained so that different teams can take the data provided by another team and understand how to use it.
  • The staff’s data literacy. To cut on guesswork and assumptions, people need to know how to interpret dashboards and get insights from marketing analytics.
  • Incorporation of data into decision-making. Actions cannot be based exclusively on gut feeling or the manager’s hypothesis. Analytics needs to play a major role before any action is taken by any team or a leader.

Challenge #2. Lack of Resources and Technical Skills

Even those teams that realize the importance of omnichannel marketing are reluctant to follow this data-centric strategy due to obvious financial and technical limitations. While data management systems are rather expensive on their own, their efficient use also requires hiring a specialized team or re-training in-house marketers to handle the new toolkit.

The Solution

  • Data management solutions are getting more flexible and thus more accessible to businesses of different sizes. It’s possible to go for a trial version or a light plan to assess whether a particular solution is fit for purpose.
  • Instead of building an in-house team of data scientists and engineers to customize and manage a marketing data system, try going for consultation provided by the platform vendor itself or specialized third-party partners. Such consultants provide all-round assistance, from picking and deploying your chosen platform to training the staff on how to use it.
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Challenge #3. Complexity of Data Integration and Management

The number of data sources is growing at a breakneck speed, with up to 15 of them in 2019:

average number of marketing data sources

With so many data sources, businesses struggle to have a unified view of their customers. When they try to integrate data from different sources, they run into a problem of matching different data formats and losing important chunks of information in the process. 

The Solution

  • Unification requires an efficient data management framework in place. In other words, the whole process from data prepping—prior to its integration—to its further management should be divided into clear workflows (data architecture, data analytics, data quality, etc.) and assigned according to the adopted data governance model. This way, it gets much easier to check whether the data is fully converted, missing, or recently audited.
  • Cloud-based solutions remove the necessity of hiring a whole new technical team to connect data across multiple sources and devices. In case you find it difficult to handle complex data management systems efficiently, consider turning to consulting services. They will help with data transformation and further management within your platform.   

Challenge #4: Data Quality Issues

Even when data is successfully integrated, there’s still the question of its quality: it can contain errors, contradictions, and duplications.

The Solution

It’s not necessary to achieve 100% clean data. With big data, for example, it’s next to impossible. However, for adequate performance, there's a strong need to maintain it on a “good enough” level and use automated monitoring solutions to regularly audit for grave errors and inconsistencies.

Here’s a short checklist for improving big data quality:

  • Prioritize your data sources according to their reliability. Always verify data from public or unreliable sources.
  • Cleanse data of duplications, non-standard representations, and unknown types.
  • Verify data against standard or customized rules before merging.
  • Run regular manual and automated data audits.

Challenge #5. Real-Time Data Processing for Instant Customer Assistance

When customers switch between multiple channels, they shouldn’t feel they communicate with different companies. That’s why they shouldn’t start from the beginning every time they switch channels. Even knowing this, businesses are still struggling to deliver personalized messages to customers based on their real-time actions across different marketing channels. 

The Solution

  • To pick up speed with your customers, let an AI-driven system capture data across all your data sources. AI can process customer actions in real time and dynamically deliver the next best action for each use case. For this, algorithms employ customers’ browsing and purchase histories as well as their interactions with a brand across all the touchpoints. You can leverage this data for listening, interpreting, and responding to a customer’s intent and then delivering personalized experience.
  • Implement omnichannel customer service by integrating chats, calls, social media, and email. Such a system will also show which channels work well and measure service reps’ work like the speed and quality of their responses.

Challenge #6. Lack of Transparency Between Different Teams Within Marketing Campaigns

Customers share lots of information about themselves through their multichannel journey, providing a wealth of data for personalization. However, when it’s all stored in silos, companies can’t get a comprehensive view of customers and have to act on incomplete information, delivering mixed or duplicate messages.

The Solution

A 360-degree customer view means getting away from the silo mentality (where information is not supposed to be shared between different teams) and linking data sources together. Sales teams need to know why the marketers have passed a lead to them. Service reps should be briefed about all the updates, releases, and promotions in order to adequately react to the rush of calls or tickets. At the same time, service reps should share alerts about opportunities with marketing and sales.

Silos are not universally bad, they are just a bad fit for an omnichannel strategy. In order to break it, companies need to:

  • Shift to a customer-centric approach. Show different departments who your customers are, their pains and expectations. Let each team see how their actions impact customer behavior and how their integrated efforts will make a difference. Meet regularly to set and discuss strategic goals and communicate them clearly throughout your internal hierarchy.
  • Kill the barriers between teams and management levels. The most comfortable way to un-silo business processes is to implement a platform where all the teams can easily contribute data and their insights to. As a result, all the channels and touchpoints will be connected, and employees who are in contact with customers will have accurate and relevant information.
  • Measure what matters, i.e. align KPIs customer-wise. Recognize and reward successful customer outcomes.
When customer information is stored in silos, companies can’t get a comprehensive view of customers and have to act on incomplete information.
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Takeaways

Omnichannel marketing automation is all about two things:

  • The mapping of customer experience across multiple channels
  • Customer data and ways to use it efficiently for personalization

Although complex and ridden with multiple challenges, omnichannel marketing automation can be mastered by employing these specialized tools, along with the overarching data-centric mentality:

  • A single platform for customer data management to store every account’s information and history of interactions with the ability to feed it with different data sources and give visibility into data to each participating team.
  • AI-powered solutions to automate customer data processing and predictive analysis to be used for customer journey mapping and further real-time personalization.
  • Scalability-friendly tools that adapt to your company’s changing needs, accommodating new channels, customer segments, or even markets.
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