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Home / Blog / Build Your Competitive Pricing Edge in the High-Tech Space
Read Time: 19 minutes


BUILD YOUR COMPETITIVE PRICING EDGE IN THE HIGH-TECH SPACE

Kamal Sabnani April 21, 2021

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In today’s world, the role of technology is indispensable. The high-tech sector
contains businesses revolving around the design and manufacturing of
electronics, the creation of software and computers, and application of emerging
technologies such as Artificial Intelligence, Augmented Reality, and Virtual
Reality.

Semiconductors form the foundational building block of virtually all tech
industries as they power many of the cutting-edge digital devices we use today.
Technology has touched our lives in many ways, some are obvious like how
smartphones have taken over our lives but some that are not so obvious. The
interactive smart devices installed at homes, computer-controlled cars that we
drive today, cloud computing and video conferencing we use today to collaborate
and stay connected, and lastly, the use of AI in day-to-day applications are
some examples of how technology is shaping our lives.  

While technology has definitely made our lives simpler, it is transforming at a
rapid pace as a result of the constant game of one-upmanship where companies are
trying to outdo one another. Smartphones, computers, and TVs are a great example
of this. New technologies and competition are causing companies to innovate and
develop products at a faster rate resulting in shorter product life cycles.
Alongside the accelerating development cycles, companies are diversifying their
portfolios by offering custom solutions to meet specific applications.  

COMPLEX CHALLENGES

To keep up with the ever-changing technology and innovation, high-tech companies
make significant investments in R&D that result in upfront higher fixed costs.
The longer a product stays in the market, the lower the share of development
costs, and conversely, the relative share of development costs increases with a
shortened product life cycle. R&D departments are therefore faced with the
challenge of constantly reducing the costs of developing new products. 

The industry also relies on minerals, metals and other commodities to
manufacture components and parts for high-tech devices. Increases in costs for
gold, silver, lithium, silicon, and other materials directly translate to lower
profit margins if these expenses are not controlled or represented in end
pricing. Most tech companies boast high economies of scale as marginal costs of
production are typically low e.g. A chip fabrication plant can cost billions of
dollars to construct and outfit but producing an incremental chip only costs a
few dollars. To drive higher volumes and to get the most out of the fixed costs,
Hi-Tech companies pass through their cost savings (coming out of high production
runs) by offering better pricing to customers that place larger order sizes.  

The complexity of the high-tech industry does not end with the products and
fluctuation in costs. The high-tech industry has the most complex supply and
demand chain structure of all. The industry relies on the use of many outsourced
design consultancy and contract manufacturers who in turn work with the fabless
semiconductor manufacturers and Global Foundries for the design and
manufacturing of semiconductor chips.  Technology supply chain managers are
under significant pressure to manage costs and minimize time to market—all while
optimizing logistics and maximizing ROI, especially with increasing budgets for
ever-growing infrastructure, development and research efforts. 

On the demand side, almost every high-tech company relies on an eCommerce and
multi-tiered sales channel model where the final products are sold online,
directly to resellers or via a specialized distributor. A common challenge with
a multi-tiered sales channel is the difficulty to manage and control pricing
across the different sales channels and thereby reduce quote cycle times and
increase win rates. 

Competitive market dynamics, short product life cycles, lightning-fast
innovation and technology development, high R&D costs, frequent changes in
product costs, ineffective pricing controls, and slow response to quote requests
put tremendous pressure on the margins, making it extremely important for
High-Tech companies to focus on the right pricing strategy to stay
profitable.   

BEST PRICING PRACTICES IN THE B2B HIGH-TECH SPACE 

As consumers, we come across different prices for the same products all the
time.  B2C companies capitalize on a range of customer purchasing variables like
channel, location, seasonality, time of the day, etc. to align their prices to
customer willingness to pay.  B2B does not have the same level of price
transparency we see in the B2C world, but the underlying concepts are not that
different: 

DO NOT LOSE SIGHT OF WHAT YOUR PRODUCT IS REALLY WORTH! 

The B2B High Tech Sector is evolving where more and more businesses are ramping
up their eCommerce presence to boost sales.  For businesses to be successful
with their digital presence, it is absolutely important to come up with the
right set of product list prices that are aligned with the market and
incorporate all the relevant value drivers, internal costs, competitive prices,
currency exchange rates and other market factors. While the list price of a
product isn’t usually the price a customer typically ends up paying, it is still
highly important to have an enticing, yet reasonable price listed on the website
for visitors who aren’t registered. Most B2B buyers will do their research and
narrow their potentials down to a short list before they start contacting
sellers for a quote. 

LOOK THROUGH THE CUSTOMER LENS TO ALIGN YOUR PRICES TO CUSTOMER WILLINGNESS TO
PAY!  

A market-relevant list price is definitely a good starting negotiation point as
we start thinking of customer-specific pricing. However, a one size fits all
pricing approach here for the entire customer base will put the company at risk
of overpricing the products to customers who are price-sensitive while too low
for customers that are willing to pay a premium.  So clearly, the best pricing
strategy here is to align the prices as closely as possible to a customer’s
perceived value of the products or services in question.  In any given industry
or application, the value can vary greatly. 

For example, the same microchip designed by a chip maker might go into a
smartwatch or a car. The watchmaker would likely be willing to pay a premium for
the chip given its role in the overall functionality of the watch compared to a
carmaker that values it lower compared to the other sophisticated chips
installed in the car. 

 Some of the best salespeople really understand the psychology of their
customers and capitalize on the differences in perceived value through tailored
sales negotiations but that’s not sustainable at scale.  To be able to do this
systematically across the entire customer base, it is important for companies to
go beyond their product functionalities and benefits and focus more on what
customers really value.  

So how do we measure customer willingness to pay? The simple answer here is
through prices customers have paid in the past for like or similar products. In
the B2B space, price is usually the output of the back-and-forth negotiation
between sales and the customer. Price negotiation is inevitable but quite useful
here as it reflects the underlying realities of the market and brings variation
in the data. 

Segmentation is a well-known concept in the pricing world.  It is the process of
clustering customers in some form of a peer group based on a set of common
characteristics.  While the idea of segmentation is quite straightforward, its
design plays an important role in the success of the overall pricing solution.
In general, here are some of the best practices every company should adopt as
they start their pricing segmentation journey. There are some nuances in the
High-Tech space that I will point out. 

REACH BEYOND THE STATUS QUO WITH THE DATA  

Most companies that embark on their pricing segmentation journey, make a common
mistake of delving straight into segmentation design without evaluating how good
or bad the data is. The main objective of segmentation is to explain the price
variation in the data by creating compelling segments using product, customer,
and transactional attributes. It’s important for companies to realize that
Segmentation is as good as the data it is built on. Companies are really setting
themselves for failure if they do not invest the right amount of time and
resources on data assessment prior to their segmentation efforts. 

Even though the overall responsibility rests under the pricing organization,
this should be a cross-functional effort where Pricing, Marketing, Finance, IT,
and Sales need to come together as a team and jointly assess the state of the
data. Data assessment allows companies to understand:

 * If the data truly reflects the pricing differences they expect to see in the
   data
 * Does the overall profitability align with internal financial reports? 
 * Does the data capture all the pricing attributes that can intuitively explain
   the pricing differences in the data?

Most companies can easily troubleshoot the first two areas; however the third
one is quite involving and what really sets one company apart from the rest. The
process of determining the most relevant and effective combination of attributes
should not be limited to what’s available in the data but should go far beyond
that.  Data discovery enables companies to uncover a lot of valuable pricing
information that is buried in the minds of the pricing, sales, and marketing
groups. 

Data discovery should be followed by data enrichment to ensure all this
information can be translated into tangible pricing attributes that could
further be leveraged in segmentation modeling. As we think about the high-tech
space, some of the key pricing attributes to capture in the data discovery
process are the following:  

 * Route to market – Companies have a multi-tiered channel strategy where the
   product is sold online, directly to businesses or indirectly via distributors
   and resellers. Each channel has its nuances so it’s important we do not mix
   routes to market. 
 * Product lifecycle – Product lifecycle plays a key role in pricing especially
   in high-tech where products have a short lifecycle. 
 * Lead time – Shorter lead times are desirable by most high-tech customers
   making this an important consideration in pricing segmentation. 
 * Customer industry / application – Customers in a certain industry might value
   a product quite differently than customers in other industries. 

BEAR IN MIND THAT BUSINESS STRATEGY TRUMPS STATISTICS 

Most organizations are made to believe that the best segmentation approach is to
completely rely on statistical algorithms. While statistical algorithms are far
more superior to humans in uncovering hidden relationships in the data, they
should not be the driving force behind pricing segmentation. It is important to
realize that blindly trusting a math-based approach can lead to nonsensical
bases for segmentation and can lead a pricing team to mistake correlational
relationships with causational ones.  Statistical algorithms are designed to
group transactions into segments by clustering on dimensions/attributes that can
explain the highest price variation. 

But if that’s done without an eye towards higher-level business strategy, the
underlying segments will surely fail to demonstrate the credibility and face
validity that is important to gain alignment and acceptance within the
organization. Best practice here is to lay out a high-level business strategy at
the top of segmentation to reflect some of the strategic considerations in price
differentiation such as different route to markets, international market
dynamics, and multi-business unit operations. 

Once the business strategy is laid out, statistical algorithms should be
deployed underneath to do more of the heavy lifting in terms of identifying
pricing patterns that are not obvious and yet less questionable.  

ESTABLISH WELL-DEFINED VOLUME PRICING POLICIES TO DRIVE RIGOR AND CONSISTENCY IN
PRICING  

Economies of scale in manufacturing make volume pricing a common practice in the
high-tech space. Volume pricing incentivizes customers to place larger orders as
they get better pricing for higher volumes. 

While some companies have well-defined volume pricing policies in place, for
others they’re often crudely defined or left at the discretion of the
salespeople.  For companies to truly understand customer willingness to pay, it
is important to decouple the volume effect from overall pricing.  While
Segmentation is a powerful framework to estimate customer willingness to pay, it
fails to correctly and systematically model the impact of volume on price.
Attempt to do this as part of segmentation will lead to:

 * Inconsistencies in the price-volume relationship reinforced by bad historical
   pricing behavior.  
 * Significant increase in the number of segments leading to sparsity issues.
 * Failure to extrapolate when deal order sizes differ from history.   The best
   practice here is to measure the impact of volume at strategic levels of
   segmentation where we are more likely to see a consistent price/volume
   relationship. 

The tech industry is the fastest-growing industry and will continue this trend
over the next decade. As tech companies compete against each other to grab the
biggest share of this growing pie, it’s absolutely important they don’t lose
sight of pricing. Negligence in pricing could not only impact their brand
positioning but could make them totally irrelevant in this highly competitive
market.  It’s high time these companies start their pricing transformation
journey if they haven’t already.

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About The Author

Kamal Sabnani is a Principal Data Scientist with 15 years of experience applying
pricing analytics and implementing enterprise pricing solutions in the B2B and
B2C space. In his capacity, Kamal is responsible to develop and apply advanced
analytical tools and data science techniques to solve complex pricing problems
in B2B. Prior to Vendavo, Kamal led pricing analytics and software
implementations in the retail and financial services sector. Kamal holds a MS
degree in Operations Research from the University of Wisconsin-Madison.

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