5 Reasons B2B eCommerce Is Different From B2C (And Why You Need Tailored Product Data Strategies)

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5 Reasons B2B eCommerce Is Different From B2C
(And Why You Need Tailored Product Data
Strategies)
The belief that B2B transactions are similar to
B2C is nothing but a widely perpetuated
misconception. Not only are the former markedly
complex, but they also bear a completely
different strategic flavor courtesy of
emphasis on product-specific data. Add the
pandemics impact on consumer behavior into the
mix, and the gap becomes even more profound.
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Sure, the core component of such an impact across
B2B and B2C domains is rapid digitization, but
that doesnt define the more granular
dissimilarities between them. B2B companies, in
the new normal, are having to micro-segment to
cater to highly fragmented markets more than ever
before. That only reiterates the requirement for
a more cohesive strategy with respect to product
data. But the same cannot be said about B2C
eCommerce, at least not in the same way. In fact,
brands doing B2B transactions might be attracted
to a long tail model where the key is product
discovery and distribution. The key to
capitalizing on such a model is mapping
product data from multiple sources alongside
understanding the business context
holistically. Jonathan Byrnes and John Wass,
from Harvard Business Review, outline that the
key to survival in the post-pandemic period and
throughout this new era is to use the data you
have readily available to identify your profit
peaks and profit drains, and rightly so. But
first, theres a need to understand why the
product data strategy for B2B should differ from
whats usually practiced for B2C. So, what are
the differences, and how exactly do these
differences manifest themselves in the form of
product data? Lets take a look. 1) The
Decision-Making Process Is More Incremental In
Nature While the B2C purchaser makes a single,
final decision on the spot, the B2B buyer
proceeds with no less than four to five
individual decisions before eventually arriving
at the final one. As such, the B2B buyer is more
skeptical and careful than the B2C one. Instead
of making immediate decisions, buyers will ponder
their needs, the needs of their customers and
competitors, taste in terms of quality and
delivery time, budget constraints, etc. All these
elements become crucial for the B2B seller to
address, thus, exhibiting the need for an
in-depth holistic product data strategy.
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• The Product Data Is More Complicated
• In general, the B2C buyers have a simple database
  of product attributes, with a straightforward
  categorization of goods, which they use to make a
  decision. On the other hand, the B2B buyers have
  a product data matrix that comprises numerous
  permutations. It is very difficult to present all
  the intricacies of this matrix concisely, but the
  consumer viewpoint is certainly as per the data
  as possible, as it pertains to their needs.
• The complexity of the B2B product data can also
  be inferred by the requirement to amalgamate
  several data sources. For instance, B2B data can
  be sourced from the companys CRM or perhaps from
  a product catalog that is being distributed to
  partners or even from a data-driven marketing
  program. This data can further be categorized as
  firmographic, technographic, intent, and
  behavioral. All these ingredients come together
  to form one complete product data structure.
• The Decision To Buy Is Based On The Products Valu
  e Proposition
• The B2B decision-making process very tactfully
  goes beyond mere product specifications. Most
  often, what the customer looks for is the value
  proposition of those product specifications, and
  not solely the product. The B2B buyer is less
  driven by the product and more by how the product
  meets his/her business needs. Thus, a holistic
  value proposition comprising product value
  and non-product value plays a pivotal role in the
  B2B buyers decision-making process.
• Also, the price factor takes a back seat in such
  transactions. The B2B strategy aims at retaining
  customers for future transactions, which can
  materialize only if the seller is capable of
  delivering superior non-product values. This
  necessitates a detailed product data strategy
  that focuses on comprehending the business
  context first.

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• The Product Data May Not Be As Visual
• Visuals play a huge role for the B2C buyer. For
  example, visuals such as those of an iPhone, a
  pair of jeans, and a laptop can make or break the
  product decision. These visuals are not only
  influential in driving sales but also act as an
  ice-breaker when done with style. The likes of
  Facebook, Pinterest, and Instagram have taken the
  world by storm for precisely this reason.
• The B2C product data strategy, therefore, focuses
  on the visualization of all products with great
  emphasis given to technical details, prices, and
  discounts. But when it comes to B2B eCommerce
  transactions, visuals may not be so important. Of
  course, companies offer insights into the tools
  workings.
• For instance, IBM or the like would certainly
  provide visualizations of the dashboard, but the
  emphasis is more on the products role in terms
  of business solutions. For that reason, most of
  the B2B products are intangible, complex, and
  specialized. What would be highly visual in a B2C
  deal quickly loses its appeal when applied to B2B
  transactions.
• The Need For Data Validation Is Greater
• The B2B data validation process is a two-way
  street. On the one hand, theres the need to
  verify whether the product matches the
  specifications desired by the buyer. On the
  other hand, theres also the need to track
  whether the specifications match what the
  product needs. After all, the seller must
  understand if his/her product is capable of
  meeting all business requirements or not,
  especially when the idea of custom solutions is
  perhaps the USP or a significant driver of the
  USP.

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• What Should A Unique B2B Product Data Strategy
  Encompass?
• Well-Rounded Product Descriptions
• The B2B data strategy must be well-rounded, as
  much as the product itself. It cant be any other
  way since holistic product description is the
  only way to comprehend the complete feature set
  of a product. To that end, heres how it should
  turn out
• Buyers business context, i.e., the question must
  be addressed What are the business needs?
• Both tangible product characteristics and
  intangible value proposition characteristics must
  be enumerated
• Images and videos must be attached to the product
  data for a more visual experience
• The product data must be kept simple and
  uncluttered for ease of consumption Readability
  must be prioritized while keeping the language
  prowess intact
• Tiered Product Information
• Product information is available in many
  permutations. It can be classified based on the
  buyers needs, or it can be categorized based on
  the products value proposition. Its not always
  necessary to display all information, but
  depending on the buyers needs, there must be a
  scalable modus operandi. For example
• If the product is a premade solution, then this
  information must be provided in one place
• If the buyer is customizing the product, then
  this information should be customized in step
  with his/her customization

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• If there are several versions of the same product
  in the market, then different versions must be
  organized with the same system of classification
• Geographical locations must also be factored
  in. If the buyer is internationally based,
  then this information must be provided in the
  same manner in all territories
• Product Lifecycle Management
• Product maintenance, deployment, and replacement
  are crucial aspects of the B2B product data
  strategy. For example, changes in the
  product can be implemented based on the buyers
  feedback. This requires a smart inventory
  management system that can track this data
  to ensure product delivery consistency.
• Issue-Tracking/Issue-Resolution/Customer Service
  Configuration
• Product issues have a direct impact on the
  buyers business. In that light, the B2B product
  data strategy must incorporate a mechanism to
  address these issues. For example, a product
  issue may have been overlooked, leading the buyer
  to incur a loss. In such a scenario, the seller
  must ensure that the buyer is not deprived of
  product delivery and/or help in fixing the issue
  on time. This can be accomplished through
  regular monitoring of the products
  interaction and associated performance.
• Conclusion
• A spate of startups and businesses have already
  recognized the same bellicosely and adapted their
  eCommerce strategies accordingly. However,
  several others, still subscribing to the
  mainstream belief, are struggling with a plethora
  of challenges that come as an aftermath of their
  misguided approach.

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At EnFuse, we believe that eCommerce product
data strategy is a crucial component of the
business growth strategy. To that end, we help
organizations make intelligent decisions while
exploring, designing, testing, launching, and
managing products. Read More Enhance Your B2B
Marketing Experience With Adobe Marketo