By Chirag Parmar
The advent of technology across sectors has helped brands accelerate their customer experience (CX) offerings. The martech sector, particularly, has seen innovations in recent times to engage customers across touchpoints. Incorporating emerging technology solutions like artificial intelligence (AI) and machine learning (ML) has helped marketers not only analyse data to create personalised experiences but also to make predictions about purchasing behaviour. Understanding customer behaviour is the foundation for successful CX. To unearth customer behaviour trends, martech professionals must continue to leverage cutting-edge, new-age technology that will help create retention solutions.
Today’s empowered customers are on the constant lookout for experiential engagement, enabling brands to re-look at data intelligence across customer journeys. However, the challenge while engaging customers is not collecting data, but deriving meaningful data that can be leveraged into actionable insights at later stages. As per Gartner, the average cost of poor data usage accounts for a staggering $14 million on a yearly basis. Here’s how enterprises can look at adopting technology solutions to further integrate data:
AI: AI helps streamline business intelligence by automating data analytics and delivering insights that are highly value-adding. With the help of ML-enabled algorithms, AI can automatically analyse data to uncover hidden trends, patterns, and insights that can be leveraged by organisations to enhance CX operations.
Blockchain: Data analysis that leverages blockchain involves understanding, classifying, and monitoring transaction data, allowing users to get valuable insights and providing recommendations for better risk assessment. It also ensures real-time analysis and traceability.
Predictive Analytics: The software solutions associated with predictive analytics can be adopted to discover, evaluate and deploy predictive scenarios by processing big data. This helps enterprises to proactively analyse possible problems with customer behaviour and CX.
Prescriptive Analytics: Prescriptive analytics creates avenues for enterprises by predicting the most favourable outcome to any given situation. It provides solutions as to what actionable insights can be undertaken to achieve aspired outcomes.
While technology can help businesses leverage data for actionable insights, the challenges arrive with data silos. A data silo is a repository of data that is essentially controlled by one department, resulting in isolation from the rest of an enterprise. This kind of disconnected data makes it impossible for marketers to gauge how one channel or data source influences the bigger picture. Thus, making it difficult to decide how campaigns should be adjusted to meet objectives. It also impairs insight into how marketing efforts are impacting revenue.
Data isolation makes it difficult to understand how marketing performance is influencing a particular company’s business operations, with 47% of CMOs struggling to demonstrate that their businesses are benefiting from marketing efforts, as per WebEngage’s recently launched report titled, ‘Death by Tools.’
Unfortunately, data silos result in:
Wasted resources and time: With the growing number of marketing channels, marketers spend a staggering amount of resources and time on different tools and technologies, instead of storing their marketing data in a centralised location if the data was siloed.
Lack of integrated performance data: With a multi-channel marketing strategy and numerous siloed analytics tools offering performance insights, it is impossible to get a comprehensive view of how campaigns are performing.
Problems with CX: As most businesses aim to create multiple touch-point for customers, enterprises have to keep track of various interactions with different departments, affecting CX operations.
Limited collaboration across teams: With data silos each team is required to work with their own data, making it difficult to collaborate and derive unified insights.
Since data silos occur with different databases that are isolated from one another, organisations can look at integrating data through the following strategies:
Using integration software: Integrating data that is located within different pieces of software and systems is the most effective way to avoid data silos. It will help marketers with a complete picture of customer behaviour and trends.
Choose a holistic third-party platform: Businesses should look at investing in an all-in-one platform that can help them manage their data in one place which will align functions in all teams but will also help users access marketing data from a centralised location, to help unearth relevant insights.
Cultivate a collaborative company culture: It is critical for companies to remember that using a data management platform won’t erase silos. Employees should be encouraged to collaborate and analyse that across platforms.
Introduce governance standards: Companies should look at setting governance standards once the data is centralised, to further ensure that new silos are not being created.
As customers adopt more innovative technology, it becomes difficult for businesses to create differentiating, experiential user journeys for customers. To derive deeper insight into customer behaviour, companies look at marketing data from different sources, hence database management is crucial. Businesses should look at avoiding data silos because it negatively impacts the customer experience. However, with the growing advent of technology, organisations can negate this by integrating different business applications.
The author os the senior marketing manager at WebEngage
Also Read: The Content Traction & Evolution : A Tech-Integrated Advertising Sector
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