The ways in which businesses connect and work together are constantly advancing. With increasing volumes of data, emerging technologies, more refined marketing tactics, and evolving marketplaces, firms can engage in new and improved ways. Here are some trends shaping B2B strategies.
Allowing big data to enable stronger analytics
Increasing amounts of available data offer firms the chance to produce greater market and customer insights, which are useful in developing and servicing B2B relationships. In industries like manufacturing, advances in sensor technology and decreasing implementation costs have facilitated the production of more data. The rising use of digital tools in the cloud and more comprehensive integration of information sources also creates and organizes increasing amounts of data for several industries, including finance and technology.
This data helps firms identify their needs, and it can be selectively shared with vendors to further augment their B2B services. It also acts in tandem with the increasing amounts of publicly available information and subscription services that offer insights on businesses and industries.
As the tools used to acquire data on markets and companies become more readily available, firms can also leverage more information in their analytics and intelligence. This better equips businesses with insights that can inform how to approach potential B2B customers and then comprehensively offer services.
Using account-based marketing in order to refine your strategies
Firms use account-based marketing (ABM) to target specific accounts through highly targeted strategies. This method is especially helpful when firms focus on one company, or a specific segment of companies, they deem to be the best fit and most likely to buy and use their services.
In order to arrive at such a set, companies conduct rigorous analysis to map out markets and prospects. Firms leverage historical data that describes features of leads, prospects, and end purchasers to train machine learning models to estimate the effects of such features on sales outcomes. These features may include industry and product classification, revenue, employee count, and a host of others. With estimated effects realized, the firm can apply prospects’ features to the models in order to estimate the likelihood they become a client – and then target only those prospects with the highest likelihood.
The strength in predictively targeting companies for account-based marketing lies in the integrity of the underlying data, and the robustness of the models. Firms should control for confounding variables to help to keep the attribution of effects on the characteristics of accounts and not other, otherwise omitted, factors at play. These processes help to identify the most valuable and highest-opportunity accounts to which resources and time should be directed.
Once targets are generated, companies use personalized marketing and sales strategies to strategically lead an account into realizing the need for their service. This process consists of custom messaging techniques and programs tailored to the account, as well as the key buying stakeholders and various decision-makers within it. The custom nature of ABM enables marketing and sales departments to function as a unit that joins digital and in-person strategies. Oracle CEO Mark Hurd relays this importance when he says the B2B, “marketing process and sales process has to integrate...It isn’t binary. You don’t have a digital process that ends and then a face-to-face process begins. They work together.”
Employing intelligent services to gain efficiencies
Automation can play a large role in the provision of B2B services. Offering a service that can provide automation-based efficiencies to other businesses presents significant value in this day and age. Firms doing so may leverage data and technology to analyze their client’s products, operations, or overall business strategies. They capture useful data on their clients, which, in turn, helps to inform the services they provide.
Trends also indicate a desire for data captured by suppliers throughout relationships to be leveraged in machine learning algorithms. These tools enable businesses to derive helpful insights that may be indiscernible to normal human realization. They further equip suppliers with a means to offer accommodative services.
In this current environment of ever-heightening competitiveness, it is also extremely valuable for vendors to quantify their services and overall impact. Doing so helps to ensure accurate, clear, and convincing expression of their value to the client. Data-driven insights delivered via intuitive reporting provide vendors ways to express their own value and convince clients of the ROI they provide.
Using digital marketplaces to connect businesses
B2B digital marketplaces are seeing upward trends in their abundance and usage. Such platforms use market-clearing rules and intelligence to help connect businesses. By leveraging data on the participants from each side, marketplace services and applications align the offerings and capabilities of suppliers with the needs and demands of requestors. These digital platforms thus connect businesses in the procurement process.
Marketplaces organize participants and help facilitate the bidding-and-agreement process for any B2B engagement (e.g., supply chain, information technology, marketing, and financial services). They can connect warehouse or transportation services with firms looking to distribute their goods. They help companies find IT vendors that fit their needs. They curate firms offering accounting and financial service offerings for businesses seeking to reap third-party efficiencies.
In all cases, these platforms breakdown supply and demand-side participants into features that help determine appropriate matches between them. For example, a given supplier may be defined by what they specifically offer, their location, pricing, capacity, technology at hand, and past performance and reviews. Those on the demand side may be defined by what they need, their location, willingness to pay, and other purchasing preferences and descriptive variables. By aligning the requests of the two sides, digital marketplaces connect parties for business. By incorporating AI and machine learning, platforms can also infer additional characteristics about participants from the given data. These inferences help further optimize matches.
Trends in data, process, and technology represent opportunities for businesses to connect. They mark changes in the B2B landscape, and we can expect them to continue to facilitate market-making, sales, and vendor-client relationships as time goes on.