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1、The B2B Evolution:Data and Customer Experience are 2025s Growth DriversDiscover the key changes to people,processes and technology that will empower you to unlock data value,reimagine customer experiences and drive growth.2The B2B EvolutionThey are often much more nuanced than what we find in B2C or

2、ganizations.Industrial manufacturing,distribution and other B2B firms can attest that transformation especially data transformation can be intimidating.73%are only somewhat effective at drawing insights from data.This means customer and staff experiences powered by data can fail to live up to expect

3、ations.But this doesnt mean that all B2B organizations are standing still on technology and transformation.B2B leaders are engaging with the latest data-driven innovation to find opportunities,save cost and to achieve growth,specifically in the areas of search,customer service and personalization.Al

4、l of which have outsized impacts on growth and cost.The latest advancements in large language models(LLMs)have unlocked opportunities around what B2B businesses can do with data to serve customers and answer staff questions too.For example,we have seen LLM-based customer service agents save organiza

5、tions millions in annual operating costs.A global CPG client was able to use AI to better predict their supply chain needs to avoid hundreds of millions of dollars of raw materials costs.Organizations that lean into this B2B evolution will win their unfair share of customers and profits.So,why are s

6、ome B2B organizations slow to embrace change?Valtechs Voice of Digital Leaders in Manufacturing Report 2024 found the top three reasons that organizations are failing to adopt digital initiatives and services are around people and culture 49%reported slow internal adoption and reluctance to change;4

7、6%a lack of cross-functional and departmental collaboration;and 46%a lack of ownership of digital at a local level.The built-in challenges and slow-changing culture of the B2B ecosystem can make it tough to implement the latest technology and ways of working.While internal resistance to change can d

8、elay progress,those who figure it out will have a significant competitive advantage.In this guide,we explore the key actions that will help B2B leaders overcome these obstacles and set their organizations up for success.Want to succeed through the 2020s and beyond?You need to embrace the B2B evoluti

9、on and put data at the heart of your transformation strategy.B2B environments are complex.Pricing structures.Sales journeys.Product types.3The B2B EvolutionContents0508101201 Make search smarter02 Set better pricing Net revenue managementQuote generation15 232631Showing contract prices in B2B ecomme

10、rce search resultsBehavioral pricing effects 03 Take time to understand your unique data needs172004 Build a solid data foundation to achieve data-driven outcomes 05 Create a winning data team06 Get in touch4The B2B EvolutionMake search smarter015The B2B EvolutionMake search smarterOne of the fastes

11、t ways for B2B orgs to use data to increase sales is by making the search experience that they offer their customers,partners and employees better.B2B organizations are known for having convoluted and tough-to-navigate search functions.But smooth search functionality is one of the clearest indicator

12、s of data maturity and one of the best ways to drive revenue through data.Simply put,the better your search works,the more sales you make,and the more revenue you will drive.This means that leveling up your search experiences should be a top transformation priority.Some level of a data foundation is

13、 needed for search to work well,and while we go into this topic more deeply in section 4,for now you need to know that for your search experience to work well at scale there are few things you have to get right.First,your product data must be governed and probably enriched,for it to be helpful in se

14、arch.Often-times the supplier provided product data,or the default information is lacking critical information the buyer needs or to even find the product in the first place.Also,you need a product data model to decide what product data the business exposes to customers.The good news is that the sec

15、ond generation of AI search is already here.Powered by large language models(LLMs),these new search technologies use natural language processing and understanding(NLP/NLU)to better map user search queries to the most relevant items.Compared to B2C,the B2B world is more complicated from a customer pe

16、rspective,often with millions of products and configurations offered.This ability to cut through the noise and help customers connect with the products they need faster is invaluable.In the past,B2B organizations often built deep custom configurations of their search stacks.Even just five to ten yea

17、rs ago,the landscape of search engine technologies was more predictable,and designed to meet more traditional(or“classical”)business strategies.In a static environment with few changes in the search technology landscape,a classical approach to search strategy with extensive optimization made sense.6

18、The B2B EvolutionApproaches to StrategyAnd the business environment in which you might use each one.However,the search landscape in 2024 looks very different.Today,LLMs and AI are creating new possibilities for search.In this dynamic environment,B2B organizations are switching from a classical appro

19、ach to an adaptive approach.In an adaptive approach,composability and automation are more powerful and flexible than extensive fine-tuning.The most forward-thinking B2B organizations are uncoupling the search vendor from the business rules and plugging in out-of-the-box building blocks for search to

20、 offer the best possible customer experience.Classical I cant predict it,but I cant change it.Adaptive I cant predict it,and I cant change it.Visionary I can predict it,and I can change it.Shaping I cant predict it,but I can change it.Renewal My resources are sverely constrained.UnpredictabilityMall

21、eabilityHighHighHighLowLowLowSource:5 Approaches to Strategy,Harvard Business Review,20247The B2B EvolutionSet better pricing028The B2B EvolutionSet better pricingIn B2B organizations,prices can be much more fluid than in a B2C business.The cost of a product may fluctuate based on the volume bought,

22、the length of the relationship with the customer,or promotions targeting specific geographies or customer types.Often depending on contracts that have been agreed with the sales team.This is one of the reasons that B2B data is so complex,but it also offers a huge opportunity for data insights to dri

23、ve better pricing,meaning that each customer gets offered the right pricing at the right time.MarketingStrategic planningAssortmentDemand forecastsTrade termEventsGap closureProcurementPromotionsNew product innovationPricing9The B2B EvolutionNet Revenue ManagementNet Revenue Management(NRM),(sometim

24、es called revenue growth management,but usually they are considered separate)is a strategy that helps companies maximize their revenue and profits over time,using data to identify and harness growth opportunities.Without NRM,this looks like setting a lower price that increases sales volume but decre

25、ases margin,or setting a higher price that leads to fewer sales but with higher margins.NRM,however,can enable customer-specific promotions and many more levers to accomplish the right mix of revenue and profit whilst offering the business more flexibility.Rather than using all these levers at once,

26、across all products and all geographies,a data-driven business will use NRM to provide clear answers for each product or service they sell.10The B2B Evolution What is the right assortment of products/services?What is the customers willingness to pay over a relevant time period?What is the right pric

27、e to charge for each customer type?What are the right volume discounts?What is the right relationship-length discount plan,if any?How long should each product be promoted?What promotions should be offered?Who should the promotions be offered to?Mature B2B organizations use data to segment their cust

28、omers and identify the likelihood of a given customer buying their product on a given day.Questions that NRM answers Customer Segment A:High likelihood Customer Segment B:Medium likelihood Customer Segment C:Low likelihoodThe customers in each of these segments should receive a different set of prom

29、otions.It doesnt make sense to continue to offer promotions to customer A,since they are going to buy from you regardless.The most compelling offers should go to customer C because buying from you is a new behavior and promotions should acknowledge and encourage this although if promotions do not en

30、courage continued buying behavior,they should reduce.Customer B should receive small promotions to keep them on track.In the NRM world,promotions are just one tool,but all of the revenue levers that you pull should be driven by trustworthy data.11The B2B EvolutionMarket research Future Automotive Ec

31、ommerce Market to expand at 24.8%CAGR during the forecast periodCar manufacturers deal with stronger barriers to change network structures in U.S.than in the EU.“Quote generationA quote is one of the most important parts of the buying experience since it signifies buying intent.The quote generation

32、process is typically handled by a commercial off-the-shelf software(COTS)application in an enterprise.If your quoting is done manually,you are losing margin to competitors who are investing in mature Configure Price Quote(CPQ)software.Enterprises usually use these CPQ vendors as they mature,moving o

33、ff of homegrown solutions that are not scaling with their businesses.They usually need deep integration with their other systems,and organizations usually prefer for this functionality to be handled outside.Gartner,Forecast Analysis:CRM Sales Software,Worldwide,Feb.2024CPQ software growth is driven

34、by demand to lower costs,improve accuracy and shorten time to quote by replacing back-office quoting functions with modern,cloud-based applications.What had previously been the realm of semi-technical sales engineers is increasingly becoming a self-service function for direct sales,channel partners

35、and even buyers.“12The B2B Evolution12 Challengers Leaders Niche players VisionariesCongaEpicorSalesforce Industries CPQScaleFluidlyApparoundYagna IQVendavoPROSSAPOracleBit2winSalesforce CPQ InforservicePathTactonCSGIn the B2B world,we need to be thinking from a procurement-aware perspective.eProcur

36、ement tooling is becoming commonplace in CPQ,specifically PunchOut,named after the term describing the buyers departure from their procurement to collect data directly from suppliers product catalogs.Most CPQs on this Magic Quadrant support PunchOut.The system integrates the buyers procurement syste

37、m with suppliers inventory system,centralizing all of their product catalogs into a single platform.This allows buyers to work directly with suppliers and can make the ordering process faster and easier than other buying methods.Punch Out catalogs make it easier for buyers to search,browse,compare a

38、nd buy products from supplier ecommerce stores because they are not leaving the controlled environment of their eProcurement,spend management or enterprise resource planning(ERP)application.B2Bs are well advised to consider PunchOut as table stakes in their quoting capabilities,as it is becoming sta

39、ndard.Ability to executeCompleteness of visionSource(s):Gartners Configure Price Quote(CPQ)Magic Quadrant,Nov.202313The B2B Evolution Sellers commerce platforms Buyers procurement systemsPunch Out means buyers procurements systems integrate with sellers commerce platforms directly,to make buying eas

40、ierPunch Out14The B2B EvolutionShowing contract prices in B2B ecommerce search resultsB2B buyers generally use seller ecommerce sites for research,budgeting,quoting and ultimately self-service purchasing.When purchasing,these customers are generally purchasing against a budget,so pricing is importan

41、t in their purchasing decisions.On the simple end,a blanket discount tier is granted to a B2B customer based on their relationship value for example.On the more complex end,the seller works out specific prices for each customer across categories of products.Finally,in the most sophisticated cases,it

42、ems are individually priced for a given customer,based on a custom configuration/configurator,their current order,or accumulated relationship value,or other factors.In all these scenarios,your customers want context on pricing before making a buying decision,and they want to see that in the search r

43、esults,including sorting by price,which is a common option that many users expect from a search experience.A lack of price context slows the decision-making process.Given the importance of price to B2B customers,providing price in product search results is key.Most B2B search platforms(ex.Solr,Elast

44、ic,Algolia,Coveo,Lucidworks,etc.)support using blanket discount tiers or a minimal amount of customer pricing levels(ex.100)for a given product.If the pricing complexity goes beyond that,a customization of these platforms(or the experience itself)is required,usually due to the 15The B2B Evolution15h

45、orizontal scalability limitations inherent in single dimensional search indexes.This gets worse as the catalog size grows;catalogs with millions of SKUs are quite common in B2B.Some traditional solutions included simply indexing a list price to support price range filters,facets,sorts and then async

46、hronously loading the customer-specific price from the pricing system as the results are shown.This is not ideal,especially when there may be large variance between the list and the customers specific contracted price.Composite indexes,horizontal sharding and extension indexes are some of the approa

47、ches used to overcome this issue.In all cases,the product/SKU data reside in a primary table and then the customer specific pricing variations either reside in a separate index or shard that is more efficiently joined upon retrieval.Also,consider a graph database or graph index as many of these plat

48、forms now also integrate advanced search capabilities and are designed to manage and retrieve across relationships,products,customers and price level nodes.In summary,there will always be cases where the pricing is too complex to even store anywhere such as when it is based on real-time criteria suc

49、h as a configuration,cart value,cart contents,relationship value,etc.In these cases,we advise to still use search to retrieve the product and potentially include it in a price range filter if that range is known.The final/quote price would then be shown typically on the product detail page,cart,quot

50、e,complete their product configuration/customizations,or as a calculated discounted value in their shopping cart.16The B2B Evolution Good$49.99$29.99 Better$59.99 Best$99.99Behavioral pricing effectsAnother aspect to optimize in B2B business when pricing individual products and packages is around hu

51、man behavior.Behavioral pricing can have a significant impact on B2B purchasing decisions,since the decision is made by humans who have human bias and behavioral patterns which are well-understood.Best value for the moneyThree months free!Price anchorPrice thresholdPower of freeOwnership effectGoldi

52、locks effectDefault nudges17The B2B EvolutionDefault nudgesPrice thresholdPower of“free”Price anchorThe most effective nudges are often“defaults,”which establish what happens if people go along with the suggested option.For example,automatic enrollment in a 401k or savings plans is a default nudge,a

53、s is automatic enrollment in organ donation.The lowest price at which selling is still desirable to the seller.13Mentally,there is a massive difference between something having even a negligible price of 1 and being free.If you are trying to give away a discount to get a bigger sale later on,or secu

54、re a long-term customer,consider if it makes sense to use the power of“free”.A price anchor is a starting price thats used as a reference point for consumers when making purchasing decisions.This psychological pricing strategy is based on anchoring bias,which is the tendency to rely on the first inf

55、ormation encountered as a reference point.When presented with multiple options,people often compare them and choose the one they perceive as the best value.24Behavioral pricing techniques that can be effective in B2B transactions:18The B2B EvolutionGoldilocks effectReference price(not on diagram)Own

56、ership effectPeople dont like extremes and often default to a middle choice.If you were selling just“Good”and“Better”options,but were to then add the“Best”,customers that had previously chosen the“Good”would switch to the“Better”,simply because of the Goldilocks effect,even if the product didnt chan

57、ge.The reference price gives the buyer more confidence to determine what is“expensive”or“cheap”.The reference price isnt necessarily something the seller can control,as B2B buying teams use many sources of information to determine what is the right price to pay beyond just the information the seller

58、 provides.Reference price could be:1)a price a buyer announces they are willing to pay for a product or service,which is often used by high-volume buyers to inform suppliers,2)average price,3)a volume-weighted average price calculated by taking all executed trades into account,4)the cost at which a

59、manufacturer or store sells a product.57This is a cognitive bias that causes people to care more about something once they consider it part of their property.This can lead to people being more likely to keep an item they own,overvalue it when selling,or buy an item of equal value at a lower price.Al

60、so known as the endowment effect or divestiture aversion.6Behavioral pricing techniques that can be effective in B2B transactions:19The B2B EvolutionTake time to understand your unique data needs0320The B2B EvolutionWeve already established that B2B environments are more complex,making the data that

61、 B2B organizations produce and gather more complex too.Here are some of the factors to consider when thinking about B2B data more generally:Vendors provide data in different and inconsistent ways.Organizations are more likely to have custom or negotiated pricing on a per-customer basis.Shipping and

62、delivery timing is critical and logistics are more complex.Tracking which distribution facility a product comes from is a high priority.Customers are likely to need precise information before purchasing since they often order products in large quantities and with specific parameters.Now think about

63、your business.What are the big data questions you need to answer to understand your data landscape?Its critical that leaders not only acknowledge this complexity but have a detailed understanding of their unique data environment.21The B2B Evolution21The big questions around enterprise data to consid

64、er:Where does your organization feel the most pain around data and insights?Where is the biggest opportunity around data?What are your customers asking for?What are your employees asking for?Which data domains are relevant to the pain points and biggest opportunities?Examples of data domains are cus

65、tomer data,supplier data,etc.What is the state of data maturity for those data domains?How much work will it take to increase data maturity to solve those pain points?Can you justify that investment?How will you measure the elimination of pain points or the achievement of those big opportunities?How

66、 do you prioritize where to scale data maturity across the organization in what order?What is the right data roadmap?What is the right technology and data infrastructure?What are the right incentives,training,organizational model,and support needed to enable your data organization?A deep understandi

67、ng of your unique data needs is essential to building a strong data foundation.Without a strong data foundation,even the most advanced technology and innovative solutions will fail to produce the business results you need.22The B2B EvolutionBuild a solid data foundation to achieve data-driven outcom

68、es0423The B2B EvolutionA solid data foundation is essential to achieving everything that we have discussed in this guide.You cannot build a smart search functionality or make the best possible pricing decisions without a robust data foundation.But getting there is no easy task.Weve laid out the comm

69、on phases of the B2B data foundation journey below.Remember,the goal of building your data foundation is not to be the best firm at data science or the best firm at data governance it is to maximize the value that data can produce for your firm based on your goals and resources.24The B2B EvolutionCu

70、rrent stateTransforming stateFuture ongoing statePeopleThere is no clear accountability or owner of data.Usually data roles prioritize making data available over making it complete,accurate,etc.Clear owners for data science,data engineering,and data governance with accountability and responsibility

71、for driving change.Clear owners for data science,data engineering,and data governance with accountability and responsibility for driving value and innovation.They also find new forms of value for data.ProcessOne-off projects to improve data quality have been done or are underway with varying degrees

72、 of success.Data activity is often shaped by what vendors provide or customers request.A strategy with a clear prioritization of foundational data,and conscious selection of local autonomy versus central authority.Change management helps to shift the culture and literacy around data.Foundational dat

73、a domains are prioritized and harmonized incrementally,starting at the most valuable.Ongoing data governance and stewardship process with teams scaled accordingly.New data has a clear intake process.Data completeness,accuracy,and timeliness are valued as much as its availability.TechnologyRandom act

74、s of data have resulted in high costs and duplication of effort.Lots of customizations have been done.Some areas of the business are more mature in data than others.Selection of more composable vendors,where helpful.Rationalization of data science and engineering tools.Tools to accelerate data value

75、 are selected or built,sparingly.Rationalizations of the data stack every 18 months.Data tools are used or built to accelerate data value.Data is democratized.The B2B data foundation journey25The B2B EvolutionCreate a winning data team0526The B2B EvolutionWhile this can be difficult and you may need

76、 to justify data team headcount,its important to remember that this team will be unlocking significant value in the organization.The ROI should be clearly communicated to executives.The team models below show how mature data teams are organized and generally how they interface with the rest of the o

77、rganization.These types of team models might be unrealistic for your budget as you grow your data maturity.So,you may need to collapse multiple roles into a single employee.Ex:maybe the Data Analyst and Data Engineer duties have to be performed by a single person for some domains.Maybe a single data

78、 analyst covers multiple domains,etc.However,it should be clear to each employee which roles duties they are performing and how the overall team is structured!The first step in building solid data-driven capabilities is to build a winning team27The B2B Evolution27 Master data Wholesale Supply chain

79、Retail Data syndicates EcommerceCentralized data team modeBest for standardizing data processesIn this centralized model,the data team is separate from other teams.The benefit of this model is that data processes are more easily standardized,because the team is directed by central leadership.Typical

80、ly composed of data engineers and data analysts,in a ratio of about 2-3 engineers per analyst,this team will also include discrete leadership roles,the number of which varies on the size of the organization.Data teamDEDADADADEDENote:DE=Data Engineer,DA=Data Analyst28The B2B Evolution Supply chain Ma

81、ster data Data syndicatesDecentralized data team modelBest for building shared services and platformsIn the decentralized model,data analysts and data engineers report to business units,while centralized data engineers report to the data head focused on enabling the platform capabilities.When buildi

82、ng up shared services and platforms,this model is helpful since it allows individual business units to continue their individual roadmaps,while the centralized data team-members provide global data capabilities.Decentralized teams can be agile in responding to specific business requirements but may

83、struggle to harmonize and maintain data sets that span across business units.Data teamPEDADADE WholesaleDADE RetailDADE EcommerceDADEDEPEPESharedNote:DE=Data Engineer,DA=Data Analyst29The B2B Evolution Supply chain Master data Data syndicatesHybrid data team modelAllows for a mix of shared resources

84、 and local-specific resourcesIn this hybrid(or“hub-and-spoke”)model,data analysts and data engineers report to business units but work closely with domain leads and other data engineer in the Center of Excellence.This model shows a unified approach to data across the organization.Hybrid teams seek t

85、o capitalize on both approaches,providing the potential for both consistency and adaptability,and optimizing business impact.Centre of excellence data teamDEDLDADADE WholesaleDADE RetailDADE EcommerceDADEDEDEDLDEDLSharedNote:DE=Data Engineer,DA=Data Analyst,DL=Domain Lead30The B2B EvolutionAre you r

86、eady to embrace change and reap the benefits of having a winning data foundation?Let us help you build a data team that suits your needs,and maximize the value that data can produce for your firm.Starting where you are,well figure out your organizations specific challenges and create a plan for movi

87、ng forward on your data journey.Get in touch31The B2B Evolution 2024 Valtech Group Holding Limited or its affiliates.All rights reserved.Valtech is the experience innovation company.We exist to change the way people experience the world through advanced digital technologies,data and design.We do thi

88、s by bringing together a global network of engineers,designers,analysts,and CX professionals with a proven ability to accelerate business growth by transforming clients products,services and systems.Our global footprint allows us to deliver impact at scale.While our nimble teams bring the agility and adaptability that allow us to create breakthrough innovation and speed-to-