THE INNOVATIVE PRICING GROUP, LLC

Pricing Practitioner Blog

**Blog Entry #1: Strengths and Limitations of “Charge Higher at Smaller Accounts” Pricing Strategies**

"Historical customer purchase volume" may be the single most popular segmentation dimension used in designing price matrix and discount structures at distributors and manufacturers. Indeed, this is typically a valid segmentation attribute, and its use in price management is appropriate and warranted. Some businesses go further, following a "strategy" of implementing relatively sharp price increases at smaller accounts year after year. This blog entry describes our views on the appropriate use of the "historical customer purchase volume" data point in price management, as well as our take on why some distributors and manufacturers eventually see "charge higher at smaller accounts" strategies run out of steam or even backfire. [Click to see full blog]+

Strengths

When distributors and manufacturers seek margin improvement by increasing prices on small-volume accounts, they are typically motivated by the following factors:

They feel there is less risk involved in increasing prices at these smaller accounts. Even if some of these customers leave due to pricing, the business has not put a key account at risk.
They feel smaller accounts may be less price sensitive:Smaller accounts may be less sophisticated customers with less negotiating power than higher-volume accounts.
Smaller accounts may also be “cherry-pickers”, buying only a small group of products they cannot obtain from their primary suppliers. Data-driven analysis can confirm: demand curves for smaller customers are often less “steep” and may be positioned along higher values along the price axis generally:

Larger customers actually expect to be rewarded with lower prices, and they may get upset if they find out smaller accounts are getting better deals.
Rewarding higher-volume customers with lower prices can provide customers with an incentive to purchase more from the business, such as by way of consolidating their purchases.
The data to compute “actual purchase volume” is readily available, without the need for additional data collection efforts.
Volume-based price differentiation is generally accepted as a legitimate (legal) form of “price discrimination.”

In fact, "historical customer purchase volume” is likely the single most popular customer segmentation dimension in devising price matrix structures and discounting schemes. Not surprisingly, several “canned” pricing solutions incorporate this dimension into underling pricing algorithms and approaches. So, why would one question the validity of such a sound strategy?

Limitations

Some distributors and manufacturers seem to be prone to continue applying the same strategy of implementing sharp price increases at smaller accounts year after year. These strategies eventually run out of steam, and they may eventually start to backfire. In some extreme situations, these actions can even drive down margins in the business. Here is why/how this happens, and what to do about it:

While the elastic/steep portion of the demand curve may be at a higher price range for smaller accounts, demand curves in these segments still do have a range of somewhat steep slope/significant elasticity:

Accordingly, “pushing price at small accounts” is an effective strategy only within a certain price range. Once price levels push the envelope too far into the elastic portion of the demand curve, the following can occur:

The distributor may start losing out on more and more real, higher-margin sales volume. This can actually drive average margins down in the business due to the mix shifting.
The small account population may include customers with higher volume potentials – however, this growth potential may not be realized if prices quoted/charged are above the market range.
Although management/analysts may be focused on other areas that seem more “strategic”, seasoned sales professionals will recognize pricing issues across all accounts they service. When they see inflated, market-irrelevant system prices, they can respond by:

Discounting, thereby reversing margin gains, often by more than necessary.
If controls make discounting difficult, they may decide to step back from actively pursuing business at smaller customers.
They often start questioning the validity of system prices across all products/all customers in the business, fueling discounting habits across their entire portfolio.

Conclusions, Implications, and Recommendations

It frequently makes sense to include “historical customer purchase volume” as a segmentation dimension in the design of price matrix and discounting structures. However, the fact that “historical customer purchase volume” is a valid segmentation dimension in a business, does not mean that “raising prices on small accounts” is a sustainable long term pricing strategy. We recommend:

In situations where smaller accounts are already being priced more aggressively, analyses should focus on predicting the impact of subsequent price hikes in these segments. Even if sophisticated pricing tools (elasticity measurements, market-responsive/self-adjusting pricing algorithms) are unavailable, analysts can get a feel for where prices may be positioned along the demand curve, by considering qualitative feedback from sales/customers, and by measuring how markets responded to recent pricing actions in these small account segments. These measurements may include reviewing company-level mix changes, small account volume trends, as well as changes in discounting practices/stick rates in small account segments in connection with previous price increase actions.
If the analysis suggests that further pricing actions at small accounts may no longer be very effective, pricing managers should refocus their efforts accordingly. Tools and strategies should be devised to capture pricing opportunities in other areas of the business - which may be quite substantial, particularly if the most prior pricing efforts focused on only the small account population.

As a final note, segmentation schemes driving price matrix/discounting structures should be refined, and they should incorporate additional customer attributes beyond mere “historical customer purchase volume” levels. While the specific list of dimensions can vary greatly from one business to another, the list of frequently relevant attributes includes customer potential, industry, location, purchase frequency, etc.

Blog Entry #2: Did Somebody Say "Culture"? ERP Implementation Failures: Implications of “Lessons Learned” for Pricing Solution Implementations

A recent LinkedIn discussion (link at the end of this posting), triggered by an industry article, featured much discussion on why ERP implementations do not go as planned. From our conversations in the distribution and manufacturing industries (and thankfully, from such conversations only), we have also become aware of pricing initiatives that under-deliver. We understand that like ERP implementations, some pricing projects never get off the ground, others produce sub-par results, and there are also some nightmare implementations that create more disruption than good. While we would not venture to guess what percentage of pricing projects under-deliver (this ratio stands at 55% to 70% in the ERP world, according to surveys referenced in the ERP LinkedIn posting), we have learned about too many instances, across most vendors in this space.

Equally striking is the similarity between the Pricing and ERP worlds in terms of the factors listed as most likely to cause implementations to fail. The below factors were cited on the ERP side:

Lacking client leadership/commitment
Generally “incompetent” client
Selecting the wrong tool to implement
Overconfidence in the vendor’s capabilities
Capabilities of solutions being "oversold"/resource needs being downplayed
Cultural barriers to buy-in

Our blog reflects on the implications of key learnings from the world of ERP systems implementations, with regards to the six topics listed above. We hope our commentary will drive deeper awareness of these topics among those with past, current, or planned involvement in the area of pricing solution implementations. Additionally, we also offer some words of advice to business leaders who may be experiencing "post-traumatic syndrome", after implementing a less-then-successful pricing initiative. [Click to see full blog]+

1. Lacking Client Leadership / Commitment

Comments from the ERP Side:

“Lack of ownership and management”
“[The client] was not committed to the project”

The ERP article asks the questions: “Do senior managers in most companies spend millions of dollars on ERP with the intention of letting it fail?” […] “Is the ‘client did not take ownership’ story just a clever way for vendors to cover up their own shortcomings?

Implications for the Pricing World:

Lack of client leadership/commitment is frequently cited as a key factor when pricing projects fail as well – but it is healthy to question the validity of this argument. In our experience, when organizations decide to implement a pricing project, their leadership teams are typically aware this is a major initiative that requires their commitment from the outset – and at least initially, executives seriously intend to commit. In fact, without such strong commitment from the top initially, a strategic pricing solution implementation is unlikely to get going to begin with. In the course of the project, this initial level of executive commitment can fade, particularly if the pricing tool proves not to live up to its promises. The subsequent discussion below reveals some reasons why this type of situation may transpire.

2. Generally Incompetent Client

Comments from the ERP Side:

“[The client] failed to carry out their project responsibilities”
“[The client] would not assign the right employees to the project”
“[The client] could not make decisions in a timely fashion.”

One observer states on the ERP side: “In a lot of cases, [clients] simply don't know what is important or how to prioritize a project. Does that make the client‘incompetent’? I think that might be a little harsh. It is up to the ‘experts’to lay out a project plan and set realistic expectations (even if those expectations aren't all rainbows and unicorns). If a vendor fails to do that,then they have nobody to blame but themselves if things go sideways.”

Similarly, another LinkedIn poster elaborated “It is too easy to point the finger at the inexpert client companies and point out their shortcomings as an easy way to deflect the responsibilities for their own deficiencies.”

A concluding thought from the ERP side goes as far as to essentially dismiss the “incompetent client” argument altogether: “While it is a given some companies need more outside help than others, most actually do have enough leadership, business skills and resources to make their ERP project successful.”

Implications for the Pricing World:

Much of the above discussion also holds true in the pricing world. We specifically find those comments from the ERP side relevant, which suggest that aside from lack of experience, businesses rarely lack the raw skills and resources to successfully implement effective pricing solutions. In the rare event that raw skills and resources are the true root cause, it may be that the particular pricing solution is not actually suitable for the business (overly complex/not truly a“fit”), and thus arguably it should have never been sold to that client to begin with.

“Experience” can admittedly be viewed as a “resource” in this area. Many clients have sufficient self-awareness to realize they do not have enough of it. This is why they tend to look for providers with substantial relevant experience. In these situations, if expert consultants (who tout their experience) do not effectively partner with clients and deliver on this dimension, then they are arguably not delivering a critical component of the value proposition their clients count on them to provide.

3. Selecting the Wrong Tool to Implement

Comments from the ERP Side:

“ERP failure starts with the selection process. It's very unlikely that your implementation will be a success if the solution you selected doesn't fit your needs. So instead of looking for scapegoats, I think it's our responsibility to educate people as much as we can.”
“Many ERP selection projects fail simply because key participants do not have the time to learn how to select ERP software. They have the capacity to learn, but lack the time.”

Implications for the Pricing World:

Like an ERP system, a price optimization solution is also just a tool that drives more effective business processes (value capture processes, in the case of pricing). The chances of success can depend on whether the chosen toolset is truly applicable (strong “fit”), and sufficiently tailored/custom-configured to align with the particular needs of the specific business.

Thanks to evolving technologies, learnings from early adopters, and an increasing body of knowledge in the area of pricing science, the landscape of price optimization solutions is a fast-changing one. As with any major corporate initiative, companies are well advised to research all their options for a pricing solution. Unfortunately, too many will only have in-depth discussions with just one or two providers.

4. Overconfidence in the Vendor’s Capabilities

Comments from the ERP Side:

“The blind faith CEOs put in third party consultants to implement ERP is mindbending.”
“[The client] saw no need or had no desire to learn the software”

Implications for the Pricing World:

In our experience, this is one of the most alarming problem areas in price optimization solution implementations. Some executives think that because a price point is derived using “optimization technology” that uses complex (often sophisticated, statistical) algorithms, and because the overall methodology seems applicable to their business model when discussed in an executive boardroom, and because there are instances where it has been deployed successfully by certain industry peers, they can blindly trust that the“experienced” vendor will configure the solution so truly “optimal” prices are generated for their business.

Reality can be quite different. Even within a specific industry(including distribution/manufacturing), there are several, markedly different scientific optimization methodologies being used with success, all of them relying on sophisticated statistical methods, and all of them appearing sound and relevant when discussed at the executive level. In fact, different optimization solutions can yield different results, depending on which algorithms are used,what model assumptions are made, and how the models are configured. The more familiar clients get with these techniques, the less likely they are to“blindly” trust any optimization algorithm (however much sense it appears to make in a boardroom setting), to stand up to the many nuances of real lifemarkets, without the business being intimately involved in picking and custom-configuringthe pricing model.

Educated clients also recognize that a “mathematically optimal”price does not necessarily mean that the price is “market-optimal”.Optimization models are just that – mathematical models that are configured to solve defined mathematical problems. In the pricing area, the term “optimized” means returning a value (price recommendation) that best satisfies the conditions of a defined mathematical model (e.g., maximizing the profit function). While the model may be complex and sophisticated, the “optimal” price will be “market-optimal” (not just “mathematically optimal”) only if model design decisions (model selection, assumptions, configuration) yield a set of model conditions that properly reflect complex market realities. To accomplish themost “market optimal” (not just “mathematically optimal) pricing models, thosewith first-hand knowledge of the market-realities need to be involved as muchas possible in specifying these model conditions. Company outsiders who mayonly spend a matter of weeks or months on a particular project, however experiencedthey may be in the industry, simply cannot do justice to this configurationchallenge, without detailed input from professionals with decades of experienceoperating in specific markets. Project risk is elevated when such knowledgeablemarket experts do not have a sufficient level of understanding of and say inmodel design decisions, so they can feel confident the model design issufficiently robust to capture the effect of most price sensitivity drivers inthe particular business. In brief, success often depends on whether the mostappropriate of optimization methodology is chosen, and how closely clients areable to partner with the vendor to ensure the model is configured in a mannerthat makes sense for their business.

Which is the “most appropriate” methodology for a given business?Current pricing practices may be viewed as sub-optimal. Due to frustration,some businesses feel an innate desire to throw them out, and “start with a clean plate”. This is understandable. Still, such a stance is often motivated by emotions and frustrations, rather than by an objective evaluation of the“pros and cons” of defined alternatives for moving forward. Current pricing practices likely came to exist as a result of efforts that involved some level of judgment and relevant industry knowledge. They are supported by current IT systems. As defective as they may be, they are reasonably well understood within the organization. Blindly adopting a new pricing methodology thatlargely ignores the status quo price structure and “changes everything”, canresult in a particularly challenging change management scenario, more complexsystem implementation issues, and/or disruptions to markets as price changesare implemented.

Accordingly, we consider it a best practice to review multiple pricing solutions, to select a methodology that can be configured to be reasonably aligned with (albeit being much more sophisticated than) current pricing practices, and to partner closely with the vendor to ensure the optimization solution is configured to reflect the client’s industry knowledge to the fullest extent possible. Chances are, successful implementations by industry peers followed this approach. Significant risk may be added to a project, if the business does not invest in learning how the optimization tools underlying their pricing solution actually operate, so they can ensure an appropriate level of alignment.

NOTE: The point is not that businesses should avoid changing up their price structures and pricing processes, if objective analysis suggests there are strong reasons for changing. We simply suggest that absent other good reasons for making more structural changes, the optimization methodology should adapt to the characteristics of the business, rather than changing up business practices to conform to the characteristics of a specific optimization methodology. Thankfully, there is a wide range of available optimization tools/techniques available today, and it is generally possible to find a price optimization methodology that can align reasonably well with current pricing practices.

5. Capabilities of Solutions Being “Oversold”/Resource Needs Being Downplayed

Comments from the ERP Side:

“Many times firm management is not frank and honest with client senior managers.”
“ERP vars/vendors are so hungry for deals due to the 10-20 year replacement cycle we placate the 'cheap' mentality by way under quoting the hours required to do things properly.”

Implications for the Pricing World:

We have seen at least three areas where pricing solution vendors appeared to not be completely “frank and honest” with client senior managers.

First, despite being marketed as “price optimization” solutions, some solutions are better described as advanced analytical tools coupled with complex custom-built price increase algorithms (rather than being real statistical, scientific optimization solutions). Recall the textbook Wikipedia definition: “an optimization problem consists of maximizing or minimizing a real function, by systematically choosing input values from within an allowed set and computing the value of the function.” In the pricing world, this typically means estimating demand curves and developing profit- or revenue-functions [“the real function”], with the objective of finding the price point [“the input value”] that maximizes profit or revenue. In statistical pricing solutions, this analysis is done at the segment level, where segments are formed by informing business judgment with the help of multivariate regression models. Pricing solutions that do not incorporate such mathematical models [“real functions”] are by definition not real “optimization” tools, but rather complex price setting algorithms and analytical platforms – unless, moving away from the textbook definition of “optimization”, one takes the view that anything “better” than the status quo must also be “more optimal”. Too frequently, when pricing solutions are sold, some client managers start out with the impression that they are procuring a scientific, statistical optimization tool, only to find out that the “optimization” tool they bought leverages statistical tools for only basic analytics tasks, such as computing means and identifying outliers.

The second is setting reasonable timeline expectations. Executives want quick results. Some pricing solutions are being marketed touting a 2-3 month time-to-value implementation period. Surely, there have been some successful projects completed in that kind of timeframe. However, this is not the norm, nor should it be set as an expectation, unless (a) the business has done tons of preparation, including data collection, cleansing, as well as legwork in acquiring substantial knowledge of the solution to be implemented; and/or(b) the approach is to deploy the solution with only “readily available” (often, not sufficiently complete) data sets, and/or (c) the status quo pricing environment is so incredibly “messed up” (think negative margin transactions, little to no previous in-house attempts to improve pricing practices), that even a quick-and-dirty pricing solution implementation can drive substantial improvement. Even for SaaS implementations, 4-6 month timeframes are more reasonable, to allow adequate time for data collection, thorough configuration discussions, validation of analytical models, and other project tasks.

Finally, the importance of “process and model alignment”(discussed above) is at times downplayed, on the basis that the price optimization solution will provide “actionable” recommendations, by way of files containing customer-item level pricing recommendations that can be uploaded into ERP systems for immediate use. These statements are rooted in reality, and consultants (ourselves included) stand behind them: price optimization solutions are great in that they go beyond “strategic advice,” generating outputs that may be deployed rather quickly in most ERPs with relative ease. Without further discussion, however, these statements can be taken to falsely imply that the nature of the client’s current pricing processes should not be viewed as relevant to optimization model selection and design decisions. Pricing vendors with canned methodologies who want to target “the world” with their solutions, and/or those that view their role as being more limited (as primarily that of an analytics provider), may be particularly less forthcoming in upfront discussions with clients on what process changes may be needed to make the solution work effectively with the client’s specific systems and processes.

6. Cultural Barriers to Buy-in

Comments from the ERP Side:

“The process of introducing and managing organizational change is where all the big problems lie.”
“[The client] did not want to deal with organizational change”

Observers from the ERP side suggested: “You need to spend a lot of time on user buy-in and the balance of new benefits versus new hindrances. Otherwise the users feel uninvolved.”

Implications for the Pricing World:

Change management and “cultural” barriers” are always on the forefront of concerns in price optimization projects.

Many pricing solutions are sold as tools that can “empower” sales professionals. In our experience as well, most sales professionals want to do their jobs more effectively, and they will embrace price guidance that is easy for them to use, that they feel is truly market-aligned, and that will help them better meet their goals and objectives. They typically decide for themselves on whether the price guidance is to be trusted based on (a) how well prices align with their own experience, including real-life feedback they get when they start using the pricing recommendations, (b) the extent to which they understand and generally believe in the credibility of the underlying analytical approaches, and (c) whether they feel that they and their peers have influenced/can influence how the algorithms operate.

Does not sound so hard – so why then, is culture so frequently cited as reason for falling short in getting the price recommendations adopted? Our experience suggests that change management becomes a true problem area only if project implementation has one or more of the following characteristics:

sales professionals are not materially involved, beyond gathering data inputs
sales professionals are asked to abandon their pricing practices and “blindly” trust new pricing recommendations instead
the analytics generally fail to deliver on the initial promises of “better,” more market-aligned (and not necessarily always “higher”) pricing
results are not being monitored, or monitoring is used only as a means to force compliance (not as a feedback mechanism to pinpoint areas where pricing algorithms might stand improvement)
incentive structures drive stakeholders to different pricing behaviors (e.g., pure volume-based incentive structures can be problematic), and/or sales professionals cannot make a clear link in how their use of the price guidance will help drive their own compensation
a reasonable migration plan is not devised (“big bang” approach).

In other words, “culture” is rarely an issue if the pricing initiative is implemented such that:

there is active involvement from all stakeholders, including the sales force
the project focuses on bolstering the strengths of existing processes where possible (rather than discontinuing old practices simply out of frustration), and on adding new easy-to-use tools
appropriate, sound analytical approaches are used, which deliver on the promises of eliminating pricing errors and yielding more competitive prices in more sensitive segments, rather than just on the promise of increasing prices/margins (i.e., the solution is not just a “glorified”, complex price increase tool)
monitoring is used not just to force compliance, but also as a means to gather market feedback on where the new pricing works well, and where algorithms may stand adjustment
incentive schemes reinforce behaviors that are consistent with project objectives
reasonable account-specific migration plans have been devised.

Blaming the inability of the team to overcome “cultural barriers” can sound like a valid excuse for sub-optimal project results. Because there is no formal owner of “culture” in an organization, it is also a convenient excuse, as no specific person is being directly or indirectly named blamed/held accountable. That said, consultants/client managers can influence the specific aspects of the project outlined above. Therefore, when the nebulous notion of “culture” is cited as a barrier, it is typically possible to define the underlying actionable issues/concerns in more tangible ways, by digging deeper into the above areas.

As the ERP observers noted before: “It is up to the ‘experts’ to lay out a project plan and set realistic expectations (even if those expectations aren't all rainbows and unicorns). If a vendor fails to do that, then they have nobody to blame but themselves if things go sideways. ”This comment may also have relevance when it comes to the “cultural” dimension: clients need to take a very active role – but, if the expert consultant downplays or falls short in supplying advice/support in the highly actionable areas outlined in the above, then is it right to blame the client for “cultural barriers” within their organization?

What to do after a less-then-successful pricing initiative?

Take a break from pricing projects, at least for a year or two. Calm the waters.

Conduct a post-mortem project review, so you can learn from the experience. Even if the project was not a success, you likely learned a great deal about pricing in your markets. Document these insights and learnings, so you can leverage them in the future.

And don’t give up. There were good reasons why you decided to try to implement your pricing initiative – and those reasons likely remain valid despite the fact that things did not go as well as planned.

The above discussion can provide for useful context for reflecting on the past, so post-mortem discussions can move to more productive topics than simply jumping on the bandwagon of blaming “old habits”, “culture”, or “not standing your ground”. For instance, if you ended up with a “glorified price increase tool” that delivered only temporary lift but no sustained results, ask:

Was the solution oversold? Did the solution live up to its initial promise, in terms being a “fit” and having a suitable level of sophistication?
Were you able to closely partner with the vendor in model design? Was a proactive approach taken to ensure key stakeholders have sufficient involvement in developing the analytical models, so the algorithms properly reflect their knowledge of the industry/specific markets (and whether mechanisms exist to ensure their continuing feedback is integrated into efforts to maintain/refine/update those algorithms)?
Was the importance of training and communication understood upfront, and not downplayed / missed in the initial project planning phase? Were there robust training and communication efforts were made to relay how the program will benefits individual stakeholders as well as the business as a whole?
Were incentives to follow the price guidance real and understood?

Additionally, if you ended up with a solution that was outright rejected by the market, ask:

Was this the right solution? Was the solution a “fit” in terms of the methodology’s applicability to the business/industry, its customizability, and its ability to integrate with existing pricing processes/structures/systems?
Was the solution provider excessively/“blindly” trusted with configuration details, with only superficial efforts to ensure market- and industry knowledge of business stakeholders would drive the selection and configuration of the pricing algorithms?
Were reasonable account-level migration plans prepared?

If you take time to reflect on the mistakes of the past, and look for ways to leverage the insights you have gained from you prior initiative, you may find yourself better positioned than you think for a fresh, successful pricing initiative!

Link to LinkedIn ERP discussion:
https://www.linkedin.com/groups/Are-ERP-Clients-Just-Plain-1896827.S.5796390380224139267

Blog Entry #3: Five Real-Life Strategies to Address Pricing Challenges from Internet Competitors in B2B Markets

The internet has increased the level of price transparency to high, unprecedented levels in many B2B industries. Customers can often, with relative ease, collect pricing information, and compare prices from websites of competing B2B suppliers.

In many instances, these changes have disrupted established B2B business operations, often testing long-standing business relationships between customers and their trusted suppliers. Some businesses are increasingly hearing from customers and prospects who complain about price points being too high compared to alternative internet suppliers. In assessing this feedback, B2B businesses frequently find that certain price points used by web-based competitors are in fact extraordinarily low relative to price levels normally seen in traditional "brick and mortar" markets.

What strategies do B2B businesses pursue, when their markets are being disrupted by such low-priced web-based entrants/competitors? The following five approaches have been proven to be effective: [Click to see full blog]+

Strategy #1: Improve How You Deal with the Complaints

These reactive/tactical approaches focus on improving the ability of the business to manage these threats when they occur. Typical tactics include training the front line on methods and processes to qualify objections, and implementing policies that provide guidance on what specific actions the business wants to take in response to qualified price objections that involve online competitors.

Businesses that purse these strategies employ a sales force that know the right questions to ask to ensure comparisons are “apples to apples” (in terms of product specifications and accompanying service levels). Front line personnel may be equipped with sample talk tracks and other means to help them convince prospects and customers that comparisons are not apples-to-apples, because significant “value add” services are being provided over and above what the online competitor may be offering. These businesses may also implement formal policies to govern the “rules of the game”, helping define when and how online competitive prices are to be matched. They may have also created processes to ensure market feedback is channeled to operations or procurement, particularly in instances where qualified price competitive seem to be at odds with the firm’s own cost positions.

Strategy #2: Collect and Analyze Competitive Pricing Data, and Take Proactive Action

These more advanced (albeit still somewhat tactical) strategies go further: a key objective now includes proactively identifying specific price risks, before they raise their ugly head in actual customer conversations.

Businesses that deploy these strategies implement processes to periodically collect and analyze pricing data from key online competitors (they may collect other data as well, including information on competitor’s breadth of selection, product availability levels, etc.). These analyses can help them better address online competitive challenges in several ways:

These data sets may be useful in immediately qualifying (or disqualifying) customer price objections citing the online competitor.

Using these data sets, the firm can proactively correct specific instances of being over-priced (over-priced meaning an “unreasonable” price gap, such as one that the front line cannot justify using "value arguments"). Correcting instances of overpricing can help lift revenues by helping the firm keep volume that could otherwise be lost, if only “reactive” strategies were in place. This is because prospects/customers may decide to buy from the lower-priced online competitor without “complaining” about the price being too high. In such situations, the firm may not have a chance to try to hold on to volume by way of reactive price cuts.

Even if some instances of over-pricing are not corrected (i.e., because the online competitor may be undercutting the firm using especially depressed price points that cannot be profitably met), upfront knowledge of these potential pricing issues can help the front line better prepare for potential customer conversations about those specific situations.

The potential costs of/financial exposures created by the use of any formal/public “price match guarantee” or internal price match policies can be modeled/understood, before such guarantees or price match policies are actually implemented.

Having full competitive data sets to analyze can enable discussions about the firm’s existing and desired/targeted price positioning vs. particular online competitors. Accordingly, firms can begin to assess what levels of “price premiums” they feel may be reasonably charged in specific segments.

Having full competitive data sets to analyze can also shed light on instances where the firm may be unnecessarily underpriced. While customers are quick to complain about prices being too high, unnecessarily low prices are much harder to detect without full competitive data sets. Several competitors with e-commerce platforms may not actually be pursuing their online channels as a means to drive down industry price levels. They may be pursuing other business strategies, such as, for instance, providing customers with a convenient self-service ordering option. Accordingly, it is often not the case that the online competitor is consistently lower priced across the board in all segments of the market. Specialty products not available from online providers may also be candidates for upwards price adjustments.

Periodic competitive price surveys can help keep a pulse on what’s happening in the marketplace. They can also enable “conscious parallelism,” where firms (legally) follow each other’s price moves in the industry.

Strategy#3: Refocus Your Business on Segments You CAN Win (and back off elsewhere)

An analysis of the firm’s competitive position vs. online market players may reveal that the firm’s value proposition/set of differentiators are likely more relevant in some segments of the market than others. In other words, some segments of the market may truly and honestly care very little about the kinds of various add-on services which, in other segments of the market, may help the firm meaningfully differentiate its offerings from low-priced online competitors.

In such situations, the firm may be measurably losing significant market share in sales of “commodity” type items to low-service segments – while other segments may show less market share losses (despite fielding a potentially equally significant level of “noise”/customer complaints). To address these challenges, the firm can choose to re-focus its efforts by directing its resources and investments to those markets where it can provide meaningful, differentiated value-adds over online competitors. At the same time, it may implement prices cuts in the commodity segments (such targeted price cuts may also be accompanied by cut-backs on service levels in that segment, such as by way of pushing commodity-buyers to self-service options).

Strategy #4: Get in the Game – Invest in Your Own E-Commerce Capability

Of course, retreating from commodity markets is not the only option – firms can try to compete for that business. However, to effectively compete with low-cost/low-priced online competitors in low-service customer segments, it may be necessary to invest in new e-commerce capabilities.

E-commerce platforms can help reducing cost-to-serve. CPQ (“configure/price/quote”) software solutions and online self-service customer portals can speed up order taking, eliminate human errors, free up sales resources from mundane routine tasks, and feed critical business data into operations and analytics (CRM, BI, etc.) systems. While setting up new sales processes may seem like a big and scary undertaking, the sales force frequently will not resist management efforts to eliminate routine tasks (the front line may continue to be compensated for sales placed through online channels, although in some cases maintaining full compensation levels may not be entirely necessary).

Getting into the game of selling into low-service segments through e-commerce may be a significant deviation from the culture and brand image of the business. To help manage these dynamics, some B2B companies have created separate online identities/brands, and their e-commerce operations may also be differentiated by product selection (less variety/possibly different SKUs), beyond just basic differences in the type and level of service.

Strategy #5: Upgrade Your Price Structures

As noted before, a key reason why online competitive threats create commercial issues for businesses is that increased price transparency exposes shortcomings in price management practices. For example, if the pricing strategy of the business has been “let’s set prices sky high, and count on our knowledgeable, profit-minded sales force, who is closest to the customer anyways, to adjust to market where necessary” - well, such a price structure will keep you from effectively competing with online competitors, as those online competitors are likely to have lower costs and more sophisticated price management capabilities. Accordingly, in implementing any of the strategies described above, success is often driven by management’s ability to make appropriate adjustments to the structural price element of the marketing mix.

What price structures work well then dealing with online competition? There is no single right answer, but here is some food for thought:

If you don’t want to compete on price, then consider a price structure that makes it more difficult for customers to compare your prices to online competitors. Let’s consider, for instance, a “list/discount” price structure, where list prices are made publicly available on a website, while customer-specific discount and rebate schemes are not. An e-commerce platform powered by such a price structure can provide customers (who understand their own discount structures) with a self-service option for getting the pricing information they may need, without making it publicly visible to competitors what true net price levels are being charged for specific items at specific customers. (As a side note, the adoption of list/discount structures can also help drive “cultural” transformations from cost-based pricing mentalities, to more market/value-driven pricing approaches).

In several industries, online competition has increased scrutiny on freight charges and freight policies. More sophisticated freight policies (where freight charges may vary by order size, customer location, product mix ordered, etc.) may help the business better compete with online players.

If you successfully integrate e-commerce technology with modern analytics tools, you may be able to “leapfrog” your competition. Technology-enabled selling platforms are often coupled with sophisticated analytics engines that dynamically generate pricing quotes, on demand, based on real-time inputs from raw competitive data sources and current “live” systems information on cost positions, availability levels, etc. In certain industries where such inputs are especially volatile, these types of solutions can provide companies with a true competitive advantage.

Conclusion

Increasing levels of price transparency in many B2B business markets are raising pressures on many businesses to improve their pricing practices. Pricing errors caused by poor price management practices are increasingly likely to actually lead to financially detrimental commercial outcomes, as they are increasingly likely to be spotted by competitors/ customers/ prospects in the marketplace. As a result, taking a proactive approach to managing online competitive threats is becoming an imperative for many B2B business organizations.

Choosing and implementing the appropriate strategy to combat challenges posed by online competitors involves multiple considerations. After understanding the dynamics of the particular challenge, updates to business process, and possibly also to price structures may be warranted. High impact, strategic threats may warrant more strategic responses.