Digital technologies create new opportunities for business-to-business (B2B) sales and marketing. They uncover a whole new world of lead generation channels for companies and organizations of every scale.
The customer acquisition process depends particularly on lead generation to identify and attract potential buyers and further prospect development. In my opinion, lead generation and prospect development are, in the process flow, inseparable.
There are five crucial steps companies must take to develop and improve lead generation and prospect development when applying data-driven technologies.
1. Build A Reliable Data Foundation
A common bottleneck for many businesses arises from complications caused by the need to combine data from various sources. Some outdated software systems simply cannot cope with the volume and diversity of disparate data. “Outdated” in this respect doesn’t just mean “obsolete.” Due to the rapid development of technologies, “outdated” means moderately lagging behind the superfast pace of innovations. The difference is enough to put the user at a competitive disadvantage. Outdated tools are inefficient, less effective and more time consuming, and they compound the opportunity for errors because they do not have the corresponding operational capacity.
Outdated sales and marketing technology includes those systems that limit your company with a legacy burden. Big data brings an opportunity to have a full-scale view of your business. However, to get big data distilled into smart data, you need to learn how to combine and efficiently analyze various types of data. Information from disparate sources isn’t easily linkable, it’s prone to dirty data and often results in unstructured or semi-structured data.
By using a data-agnostic technology platform, you can typically avoid data integration, compatibility and performance issues due to those platforms’ inherent nature to handle and process various data types and formats. This approach also helps steer clear of unforeseen operating costs and dampened scalability issues associated with being confined to only a select group of data types or formats. Additionally, keeping data safe with today’s heightened security threats requires an up-to-date and secure platform architecture.
2. Translate Big Data Efficiently
The “big data bang” has created torrents of terabytes. This data covers a wide spectrum of information that can be used by companies to fine-tune their business strategies. However, for optimal information gain companies must develop “data translation” skills.
Companies that are successful in translating big data into market growth tend to follow three basic principles:
• They use analytics to identify valuable business opportunities.
• They turn these insights into actions, products or services.
• They successfully present these actions, products or services to their clients.
Companies that apply big data and analytics in their business operations demonstrate a considerable improvement in their productivity rates. Being able to translate and make sense of data transforms big data into smart, actionable data that delivers quantifiable business results.
3. Apply Data Analytics For Performance Improvement
Data analytics is revolutionizing B2B marketing in four major ways:
• Radical improvement in quality lead generation.
• Better matching of customers to product and/or service offerings.
• Maximization of the customer lifetime value.
• Optimizing dynamic pricing strategies.
Smart applications and platforms use machine learning and data science algorithms to analyze data insights, providing sales with an opportunity to have valuable information right at their fingertips. Smart “translators” disclose the value of data by providing insight to locate, qualify and contact the most promising leads at the right time. Prospecting solutions help optimize lead generation and prospect development to operations performed in a few clicks.
4. Utilize Propensity Data
Lists of valid and accurate leads facilitate the prospecting journey and accelerate your sales process. Purchase propensity (the future likelihood to make a purchase) can help further specify your target audience to only include those with an immediate propensity to purchase your product or service.
Propensity modeling is applied to correlate customers’ characteristics to their propensities or anticipated behavior, aiming to determine the right moments and conditions to engage, affecting a prospect’s decision-making process. Propensity modeling in combination with business contact information helps to further develop a targeted sales strategy.
5. Ensure Data Quality
Data quality is fundamental; it’s as much of a truism as “garbage in, garbage out.” Don’t expect superior sales with inferior data. B2B leads are at the heart of a successful marketing strategy. Data degradation is a severe challenge for any marketer. It is crucial to make sure your data is accurate and verified.
The quality of data used by organizations has a considerable impact on its overall effectiveness and efficiency. Is the right decision possible without a reliable and accurate background? The answer is obvious — no!
To summarize, your insights drive your actions. Without data, your business is operating on assumptions and opinions. Data and analytics techniques have introduced efficiency and optimization to numerous processes. It may seem strange or even frightening to let technology take the steering wheel of your business. Yet, when implemented correctly, the empirical effect of solid data reinforces a virtuous cycle of success through increased marketing return on investment (ROI) and improved sales.
Marketing and sales teams are under constant competitive pressure. Following the basic principles outlined above will help guide them on the right track.