Data will be the holy grail for business success in the future. It will empower revenue enablement teams to respond quickly to consumer trends, identify new growth opportunities, and navigate the challenges in a data-driven marketplace. Discover some pathbreaking trends that will help businesses create a robust data-first culture within their sales enablement teams.
What’s common between next-gen enterprises like Netflix, Amazon, Uber, and Google? All these technology behemoths are data-first companies. They have set up their shops on the bedrock of data and are successfully using it to skyrocket their revenue. The power of data, if harnessed correctly, can transform smaller companies into industry giants leaving behind other prominent players in the industry within no time.
Data can help the marketing and sales teams to identify ideal prospects, address their pain points, engage effectively, and drive maximum revenue. One of the critical factors to drive business success among organizations is their ability to serve customers to their utmost satisfaction. For this, they need to understand their customers’ pain points and preferences to deliver products or services that will meet their requirements. This is where the data-first culture helps them take the lead.
Data will be fundamental to achieving sales success in 2023 and beyond. It will empower revenue-facing teams to respond quickly to consumer trends, identify new growth opportunities, and allow enterprises to predict and navigate challenges in an otherwise disruptive economy. Forward-looking enterprises will implement smart practices to make the best use of data and extract actionable intelligence from it. Let’s look at 5 key data trends that businesses need to watch out for in 2023:
Database management will become a staple business function
Modern enterprises and their top leadership now realize the value of data in business. They will be investing heavily in AI/ML-led technologies to collect deep market intelligence and use it to optimize their sales enablement functions. It is estimated that around 76% of global businesses will shore up their investment in data and BI analytics capabilities in the next two years.
AI/ML-led data management practices will rise
The use of AI/ML technologies for database management and data cleaning services is becoming increasingly prevalent among vanguard organizations. Businesses will use these technologies to automate repetitive and complex data management functions. It will also help improve the accuracy and productivity of the complete data value chain. By the end of 2023, around 45% of manual data management tasks will be automated with the help of AI/ML and advanced RPA technologies.
Natural language processing (NLP) and conversational analytics: NLP, and conversational analytics will enable end-users to ask questions about data using natural language query (NLQ). It will also enable them to receive visualization and explanation of business intelligence. NLP and conversational analytics will transform the AI-based models to make them more human-like and go beyond routine algorithms to deliver personalization.
Use of semantic data catalogues
As businesses capture data from disparate sources, they unintentionally create data silos. This makes it difficult for the marketers and sales reps to access, analyze, and monitor data and its history within all customer management systems. A semantic data catalogue will assist enterprises in overcoming this challenge. They will be able to harness the knowledge graph model encoding a semantic layer to draw relationships between data and standardize the datasets coming from disparate sources. It will help data analysts build accurate datasets and curate them for clear understanding. It will become pivotal to data management activities vis-à-vis enhancing data governance, data cleaning service, data quality, and more.
Whitespace discovery with predictive capabilities
In 2023 and beyond, B2B database providers will deliver tech-enabled whitespace discovery to identify the untapped and unutilized gaps within existing customer databases. This will involve using advanced BI analytics to navigate to sift through heaps of firmographics, technographic, demographic, and contact data to recognize the unmet requirements of existing or potential customers.
Whitespace discovery involves the assimilation of huge data volumes and eliminating the clutter to enrich the data. And finally, predictive analytics along with propensity models will be used to define the lead nurturing buckets, predict future data trends, and build an insights-based decision-making process.
Unified data management program
One of the most dominant data trends of 2023 will be the alignment between data management and marketing outreach programs. In order to get the most out of their data, organizations will have to develop a marketing program that continuously engages and cleans the data as part of the process. Let’s look at some prominent trends that companies will have to follow to keep their database refreshed and relevant:
Data profiling: It will help enterprises regularly segment, track, and refresh relevant influencers and key decision-makers within their existing databases. It will also enable their marketing and sales teams to collect net new entity and contact data from the ideal customer profile ecosystem.
Data maintenance: Since data is obtained from varied disconnected sources, enterprises must standardize them before integrating them into their customer management systems. Advancing into 2023, automated technology-led data maintenance will be key to removing inconsistent, duplicate, or inaccurate data from the system. Enterprises will leverage automated data cleansing, data deduplication, and data standardization engines.
Data validation: Another key trend to keep the database updated, accurate, and relevant will be automated data validation and refresh practices. It ensures that data is validated and enriched with new insights helping businesses to build personalized and targeted marketing campaigns.
With the growing importance of data among businesses and the advancements made in data collection and storage methods, undoubtedly, the future of database management is automation. Enterprises will be able to simplify complex and repetitive tasks with the help of AI/ML and NLP technologies. Tech-powered systems will also enable them to manage their data more effectively to gain a strategic advantage over their competitors. Vanguard organizations will continue leveraging data and BI analytics to bolster their topline and bottom-line. Others will integrate it in their sales enablement processes to build actionable strategies and wade through future challenges in a data-driven economy.
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