[Sales & Marketing Success] The Need for Data Accuracy
- Data is the single most valuable resource that a business can utilize to make better strategic decisions
- The internet is responsible for producing astronomical amounts of data every day that companies can capture and analyze for better market understanding
- Data-driven marketing can drive better lead generation and helps personalize sales and marketing campaigns
‘Data is the new oil.’
The online streaming app Netflix devoted six years to developing a data analysis algorithm to launch its first show in 2013.
To ensure its efficiency, Netflix employed two crucial elements: view preference knowledge and understanding of viewing habits.
Amazon utilizes a data-driven AI algorithm that predicts customer demands, evaluates supply availability and optimizes its supply chain. Acquiring and analyzing big data eases the process of understanding consumer patterns, thereby augmenting internal efficiency.
Likewise, collection and analysis of data aid in lead generation, increasing customer reach and dealing with competition.
A data-driven approach is indispensable for making informed decisions, thus optimizing business performance.
This blog discusses the importance of data analysis for building better sales and marketing strategies instead of relying on trial and error.
Data as a Resource
Data and its analysis are the new frontiers for competition, innovation, and revenue maximization.
Leading entrepreneurs in every sector are now putting their focus on big data and not just minute data-oriented analysis. The power to decipher valuable sales and marketing information from collected data can help companies boost their operating margin by about 60%.
Facebook aims to increase its operational efficiency by collecting about 4 million GB of data in one day.
Depending on the variables that trigger business interest, data can be categorized into four different groups:
Demographic data collect information about groups of people according to specific attributes such as age, sex, and place of residence.
Technographic data measures the contribution of technology in generating positive sales opportunities. It involves examining a company’s technological stack, which includes its hardware, software, and applications.
Chronographic data studies the intrinsic changes businesses can undertake to find high-quality leads. It also provides information on significant changes in funding or acquisitions, etc.
Intent data studies customers’ buying patterns and interests to improve their purchasing experience.
Qualitative data can provide valuable information about a business’s working culture and customer patterns.
Quantitative data gather objective information on sales, expenses, and revenue figures that helps measure the performance of specific departments.
B2B sales and marketing teams utilize data collected from websites or 3rd party resources to make informed strategic decisions and understand changes in demand for a product or service.
Like human or financial resources, the cost of acquiring data varies on the business model and may include tracking transaction details, online surveys, etc.
The Importance of Data
Businesses employ data to create value.
Data enables the collection of more detailed information on variables that define or affect the performance of sales, marketing or management segments. Here are five reasons why data collection is imperative to business growth.
1. Transforming Lead Generation
Converting your potential prospects into customers is indeed a daunting task.
Before businesses could realize the tremendous power of data, lead generation was facilitated by studying sales figures or mere estimation of key variables. Thanks to data analytics, lead generation for sales has undergone a complete makeover.
Data is transforming lead generation in several ways. One of the most significant ways is through the use of data analytics and machine learning algorithms to identify and target potential leads.
Data helps predict behavior and buying patterns of their potential prospects through lead generation algorithms.
Analysis of data obtained from these algorithms helps sales and marketing teams to convert leads into opportunities. Analyzing data thus helps gain more insight into customer segments and improves retention.
Data-driven marketing techniques have assisted about 86% of business executives to obtain an increase in return on investment.
2. Targeting the Right Customers
Creating a purchase intent for an actual product or service is crucial. But how do you understand your target customers without even launching the product?
Data can help businesses target the right customers by providing insights into customer behavior and demographics.
By analyzing data such as purchase history, browsing behavior, and demographic information, businesses can identify patterns and trends that can help them understand their target market better.
This information can then be used to create effective marketing strategies to drive sales pipeline, as well as to develop products and services that better meet the needs of their target customers.
Additionally, data can help businesses identify new markets and opportunities by identifying untapped customer segments and identifying areas where there is a high demand for their products or services.
3. Radical Change in Your Communication Processes
Experts believe that a data-driven approach to communicating with potential prospects is essential to succeeding and growing sales.
Understanding data from various channels can help sales and marketing teams identify the best times to send messages and the type of messages that can effectively hook your customers to your content.
An effective communication strategy can boost sales by 68%.
A common tool adopted by numerous companies for communicating directly with online traffic is a live chat or a chat-box application.
Live chat applications can communicate directly with customers and understand their requirements. Data obtained from these applications, subscription forms, and pop-up messages transform your communication strategy.
McDonald’s utilizes their data-driven decision logic technology to optimize operations and to communicate with their customers better. Coca-Cola uses their online brand presence to understand and identify the right customers.
4. Analyzing the Sales Team’s Performance
Business entrepreneurs believe that data analytics has revolutionised sales teams’ performance. Data helps you to adopt an optimistic approach to handling your sales pipeline.
For example, a typical sales analysis system uses data to define your primary sales objectives and KPIs to create reporting systems that can upgrade your forecasting ability.
More than 57% of sales personnel spend a significant amount of time with Customer Relationship Management (CRM) applications.
Analytical CRM tools, in particular, can raise productivity by 29% thus helping sales teams to meet their monthly targets. Moreover, these data highlight the potential improvement areas, so your in-house teams can work on them through training.
5. Targeting Your Marketing & Sales Campaigns Better
Ever wondered why a majority of websites allow your browser to send specific information?
Business enterprises utilize data collected from cookies and embedded links to develop new services, improve usability, and judge the effectiveness of their sales or marketing campaigns.
Data helps businesses to personalize content and show information or advertisements strictly based on your preferences.
Sensitive information like browsing location, contact information, and access to audio recordings allows businesses to ease trendspotting. Data collected helps you to make content that resonates with your target customer’s lifestyle, interests, and online activity.
Additionally, data-driven sales and marketing strategies create huge opportunities for up-selling and cross-selling your products. You can utilize the post-sales data as valuable insights to keep your customer engaged.
Data-driven approaches allow the board of directors to make concrete budgeting decisions.
Analyzing data provides definite information on statistics like click-through rates, view count for online content, and acquisition costs per customer.
Analysis of post-pandemic data reveals certain anomalies in B2B customer behavior.
An unobvious bias towards digital platforms bears testimony to the fact that 90% of businesses aim to sustain their hybrid sales structure. Tech giants are eventually aiming to transform their user experience based on data obtained from various sources.
Disney employs machine learning models to improve customer services as well as commit to fraud detection and content personalisation.
Smart entrepreneurs rely on data analytics to upscale their sales prospects through value propositions. Evidently, the data analytics sector is set to create more than 11 million career prospects by 2026.