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轴承的基本代号表示轴承的基本类型、结构和尺寸;前缀表示轴承零件置于基本代号之前;后缀表示轴承结构形状、尺寸、密封、保持架、公差、游隙、热处理、包装、技术要求等有改变时,在轴承基 本代号后添加的补充代号。轴承前缀、后缀代码比较复杂,数量众多,但有一定的规律性,如某些后缀在各个品牌里是通用的,但特殊的情况也比较多。以下是捷邦为大家介绍的进口轴承后缀等知识。

目录


1st party data
This is the good stuff, the richest source of insight into your ideal customer—data that’s collected, owned, and managed by your organization. It’s the data collected by you, from your audience and customers, and stored in your systems.
So, technically, it should be the easiest to learn from and activate, but without something to connect your siloed systems (like your marketing platforms, CRMs, POS systems, ERPs, contact center databases, etc.), it’s not so easy to tap into.
2nd party data
This is data that consumers provide to another company that—with the consumer’s notification and consent—you may access through a partnership agreement. Put another way, it’s someone else’s first-party data.
For instance, you could broker a deal with an airline to share loyalty card data to improve your targeting.
3rd party data
This is data that was collected on other sites, platforms or offline, by…you guessed it—a third party. Third-party data is used extensively by companies to better understand their audiences and to better target prospective customers.
It’s great for demographic, contextual, and behavioral targeting. Like if you needed to reach an audience of 24- to 36-year-old males who love wine but not cheese.

A


Ad exchange
A marketplace where advertisers and publishers buy and sell ad inventory using automated processes like real-time bidding (also explained later). Two you might have heard of are DoubleClick Ad Exchange and OpenX.
Ad server
Ad servers store ads, serve them to publishers and their website visitors, count the clicks and generate reports.
There are ad servers for publishers as well as advertisers, though the technology is roughly the same. The reason they have different ad servers is to gain greater control over inventory and reports.
Ad suppression
This is when you exclude a list of people from receiving a certain ad or campaign.
For instance, if your online and offline data was connected, you could make sure your current customers don’t get exposed to your first-time buyer promotions. So if you’re offering a three-month free trial to prospects, you can ensure current customers aren’t exposed to the ad.
Addressable TV
This is technology that lets you show different ads to different segments of TV audiences within the same program. Those segments could be defined by behavioral, demographic, and geographic factors from 1st, 2nd, or 3rd party data sets.
Addressability
To interact with a customer on a specific marketing channel you need a way to reach them—you need an address. In the offline world, this is simple—to send an email, you use an email address. To send direct mail, you use a postal address. In the online world, addresses are anonymous, tied to devices, and changing all the time. This makes it hard to reach the same customer across channels and devices with a consistent message. That’s where data onboarding fits in.
Analytics
In technical terms, this is the discovery and sharing of patterns in a particular data set. You use it to understand past activity and make informed decisions future activity.
But whatever the agenda, it’s important to bear in mind which data set is being analyzed. If you’re measuring the impact of online ads on revenue, you need a unified view of online and offline customer activity to be sure you’re measuring the offline impact of those ads too.
API
An ‘Application Programming Interface’ is a sort of window into other platforms or applications.
It’s the set of predefined commands, functions, and protocols that programmers use to interact with (and build on) another system. The data-driven marketing world couldn’t work without them.
Attribution modelling
If someone saw a banner, a Tweet, a TV ad, and a magazine ad, how can you tell what led to their decision to buy?
The basic aim of attribution modeling is to figure out which marketing actions or channels contributed most to a certain customer action.
It’s about using analytics to give credit where credit is due, and knowing how much credit is due. This gives you the data you need to optimize everything from budget allocations to messaging to campaign strategies.

B


Big data
A broad, catch-all term for huge amounts of data that can’t be processed using old-school tech. When people talk about it, they’re usually trying to say:
  • ‘A whole lot of data’
  • ‘A bunch of different types of data’
  • The ocean I’m sifting through for a few drops of insight
  • Or all of the above – and it’s streaming in relentlessly.

C


Closed loop analysis
Old-school digital campaign optimization was based on clicks and impressions. Now it’s possible to measure the impact of digital marketing on what really matters—sales.
The key is anonymization. When purchase data is anonymized, it can be linked with campaign exposure data (info on which devices were exposed to an ad or website).
Now you have an end-to-end picture of your campaign you can use to measure sales lift.
Cross-channel/Multichannel/Omnichannel marketing
This is where you reach the same customer on different marketing channels with a single campaign. Joe sees a display ad on Facebook advertising a new pair of shoes from a brand he likes. The next day, he sees a video ad on Yahoo for free shipping on that same pair of shoes. The week after that, he receives an email with a 10% off coupon for those shoes, and chooses to buy them at the mall the following weekend.
Multichannel marketing is usually used to describe the strategy of using many different channels, but the individual channels still behave independently of one another. So Joe and Maria see the exact same offer on Facebook, the website and in their email. They can then choose to buy that product via an e-commerce site or in-store.
And then there’s omnichannel marketing. This is used to describe an approach where you try to create one seamless experience across all your marketing and sales channels. Joe has a consistent experience across Facebook, Yahoo, the website and the store and can interact with any channel from the other (using their smartphone while in your branch to print out an offer coupon, for example).
Cross-device marketing
This is where you reach the same customer across different desktop browsers, smartphones, tablets, and other internet connected devices. Joe saw a display ad on Facebook on his smartphone and then a video ad on Yahoo on his laptop. The ads could be part of a cross-channel campaign or multichannel strategy.
Confused
Cookies
These are the little pieces of data that a website sends through a user’s browser to recognize a device for a future visit. They’re mostly used to relay information about a user’s portrait and previous activity on the site—things like how many items were in their shopping cart.
They can also be used to connect the marketing platforms in your tech stack based on matched data sets.
Customer ID code
When any marketing system interacts with a customer or a prospect, they give that customer a unique ID code.
The trouble is, when different systems give different codes, you end up with multiple codes for the same customer. That’s why your targeting software doesn’t know it’s dealing with the same Joe as your personalization software.

D


Data integration
Annoyingly, your data lives in a bunch of disconnected systems. Data integration is the process of combining data sets that live in different applications so you have a unified view of your customer.
There’s a lot to think about. In addition to field-naming conventions (think “F.Name” in Data Set 1 vs “First Name” in Data Set 2) or alias values (CA vs California), you also need some way to recognize that Janet Smith (maiden name) and Jane Johnson (married name) are actually the same person.
The picture gets even more complicated when you want to start matching offline records to online data, like the digital ads that Jane was exposed to. To put these data sets together, you need a privacy safe approach to recognition and data connectivity that anonymizes your records before matching and linking your data.
Data matching
This is the act of connecting entities (say, your customers) in one data set to their corresponding ID codes in another data set.
For instance, you could match cookie data from your website to CRM data about your customers and make sure Joe Customer gets treated like Joe Customer deserves, whenever he’s on your site. To comply with privacy regulations and best practices, offline data needs to be anonymized before it can be matched to online devices or digital IDs.
Data onboarding is when you match data collected offline to data collected online.
Your offline customer data can include first-party information, like purchase data (collected in-store) or call center data, and third-party information like demographics and buyer propensities.
This offline data is matched to online devices and digital IDs in a privacy-safe way, then delivered to the ad platforms, DMPs, and social channels where you run your campaigns. The process enables more strategic cross-channel and omnichannel campaigns.
Data Quality
The thing about data is that it’s usually pretty dirty. Different systems write dates in different ways. The addresses stored in your database become irrelevant when your customers change homes. There’s a whole lot of ‘erosion’ and variability that’s really important.
Data hygiene, or data cleansing, is the process of fixing all these glitches and making sure all your data complies with your own set of standards.
Data-driven marketer
An evolving species with remarkable resilience; capable of withstanding immense technological fragmentation to give customers and prospects better experiences.
Adaptable, highly intelligent, and easily distracted by shiny new channel opportunities, the data-driven marketer feeds on the fruit of the conversion tree.
A ‘Data Management Platform’ sounds simple enough. It’s a platform for managing data, right? Pretty much.
DMPs evolved out of a need to analyze the data collected in the anonymous cookies that are collected by websites and DSPs. They allow you to build segments—using behavioral data from your own campaigns and/or a 3rd party—to target specific audiences with the right ads.
They centrally manage and present all your campaign activity and audience data to help you optimize your media buys and creatives.
When combined with data onboarding, DMPs can become even more powerful. Data onboarding connects your offline customer data with the online data stored in your DMP so you can target more effectively and build look-alike models that help you reach more consumers who resemble your best customers.
A ‘Demand Side Platform’ is software that automates the buying of display, video, mobile and search ads for you.
It automates the grizzlier bits like targeting the right audiences, buying the right impressions in real time, delivering the right creative, and finding the right publishers.
Dynamic creative
Imagine a normal creative and then explode it into all its component pieces—the copy, the background image, the size and color of the call-to-action button.
Dynamic creative is able to cycle through different combinations of these components, optimizing the whole thing in real-time for every viewer.
So you could have a banner featuring that 24- to 34-year-old male that loves wine transform into a 55- to 65-year-old female who loves it too.

E



L


Look-alike modelling
This is an incredibly smart way to expand your audience and extend your reach. It’s where you (and your 3rd-party data provider) analyze your current customer data to come up with a target audience segment of people with similar behavior, demographics or preferences.
If single mothers who love Battlestar Galactica and Brazilian Coffee are sweet spot customers, you could make sure your next campaign reaches more people most likely to fit that bill.
By connecting your online and offline data, data onboarding makes look-alike modelling a lot easier.

M


1:1 Marketing
As the scale of marketing efforts grow, and the granular targeting capabilities of online channels evolve, it’s become clear that marketing both needs to become—and can become a lot more custom.
1:1 marketing is about delivering experiences that have been customized to cater to the likely preferences of customer, rather than broad segments.
Marketing stack
Your marketing stack is essentially all the technology you use to manage your marketing activities. The ‘stack’ is an old technology idea that aims to order things by ‘layer’.
Roughly speaking, the marketing stack starts with technology used to store, manage, and analyze your data. This is what’s often called ‘the data layer’.
On top of that, you’ll usually find technology to execute and optimize and manage campaigns. Your ‘application layer’ includes marketing applications that are increasingly delivered as ‘SaaS’ offerings, as well as media platforms, like Facebook, Google, Twitter, and Yahoo.
To get maximum value from your data and technology investments, you need a ‘connectivity layer’ that connects your data to your applications and media platforms. Connectivity ensures data can be used to drive better experiences and results and also provides the marketing team with the flexibility to add in or swap out applications at will.
Match rates
This is the number of records in one data set (say, customers in your CRM) that matched up with the records (say, online devices) in another data set, expressed as a percentage.
So, for instance, our average match rate for data onboarding is around 30-55%. That means that if you have in-store purchase data for 1,000 people, we can match 300 to 550 of those records to one or more online devices or digital IDs, for targeting and attribution analysis. (We know, right?)
Mix optimization
When your marketing spans multiple channels, you have to be smart about how you invest in different media. If search isn’t getting the results you expected, where should you reinvest that media spend?
Mix optimization is about analyzing what works and what doesn’t (as well as how different channels impact one another) so you can optimize the distribution of your media spend for maximum impact.

N


Native advertising
Not to be confused with content marketing, native advertising is a type of advertising that’s made to look and feel like an organic part of the platform it’s on.
For example, a native ad in an online newspaper will look like other articles, but with a clear indicator that communicates the reader is viewing sponsored content. Similarly, native ads in social media look like other content, but with a ‘sponsored post’ flag.

O


Offline data
This is data that’s collected and stored in ‘offline’ systems, like CRM platforms, point of sale (POS) systems, email marketing platforms, and contact center applications. Typically this data is tied to some form of personally identifiable information (PII), such as an email address, name and postal address, or customer ID.
A lot of marketers have struggled to integrate this offline goldmine into their online marketing and cross-channel attribution efforts. Data onboarding solves this disconnect.
Online data
This is the data that is collected and stored in digital marketing platforms such as DMPs, DSPs, and ad servers. Online data is typically tied to anonymous devices through cookies or mobile device IDs.

P


Programmatic advertising
In order to do away with the inefficiency and errors that stemmed from those pesky humans negotiating media buys, programmatic advertising (or programmatic media or programmatic marketing) was invented.
It automates the buying, positioning, and mix optimization of media inventory, making real-time decisions about price, placement, and timing, based on rules you set.

R


Recognition
In the offline world, this is the science of knowing that Robert Fredericks, Bobby Fredericks, and Bob Fredericks, Jr, who lived in Kentucky and moved to Ohio, are all the same person. This is key to integrating and enhancing customer databases.
In the online world, recognition helps you know which desktop browsers and mobile devices are connected to the same anonymous user. This is key to cross-device and cross-channel marketing.
The difference between retargeting and remarketing
Data onboarding uses both offline and online recognition to match customer data to the right online devices and digital IDs. Anonymization is a key step in the process, ensuring data flows are privacy-safe.
Retargeting/Remarketing
Retargeting technology lets you reengage with people who’ve already interacted with you, using creative that reflects their previous interaction.
So if someone’s been on your site and browsed blue shoes, your banner placements could carry a message encouraging them to come back for those specific shoes.
Retargeting (CRM)
CRM retargeting (a.k.a. offline retargeting) is about targeting customers (using the data in your CRM) with media buys that extend your campaign’s reach and reflect what you know about those customers.
RTB
‘Real-time bidding’ is the automated system of auctioning media that happens between publishers and advertisers.
It’s another one of those smart ways to keep the pesky humans out of the media buying nitty-gritties.

S


Secure
What everything—every process, every tool, every communication—needs to be if it’s going to involve your customer’s data.
Segmentation
Instead of talking to your whole audience like one big, homogeneous blob, segmentation is about dividing your target market into meaningful chunks based on preferences, behaviors, past activity, and demographics.
It’s the cornerstone of marketing and taken to it’s natural extreme, it leads to the segment of one—or 1-to-1—marketing.
Self service
A self-service model allows users to access and manipulate their service directly.
Innovation has exploded in the area of marketing technology, but IT rarely has the bandwidth to take on even more systems, and IT will never have the domain expertise that you have as a marketer.
That’s where self-service tools and dashboards come in. They replace the need to manage things like data using code, with simple point-and-click interfaces that marketers can use to solve their own data problems.
Social data
This is data that users share via social media—explicitly or implicitly through their behavior. The great thing about social data is that the user expresses all of it, so it’s far likelier to be an accurate representation of them.

T


Tag management
Tags are bits of code that live on your site and do things like collect data for analytics, cookie visitors, serve advertising, and more.
The trouble is, you’ve got lots and lots of tags for your integrations with different platforms—and tags go out of date, conflict with other code on your website, and cause security problems and slow down load time. In short, they can be a nightmare.
Tag management software does smart stuff like making sure the tags don’t load before your site’s content does. If you make a change to the site, you don’t have to change every single tag one at a time.
Targeting
Targeting is the process of using customer data to shape distinct segments out of your audience and then pursue them with distinct experiences.
This can be incredibly hard to do when your customer data lives in silos, separated from the platforms you use to engage with your customers.

V



Y


Yield optimization
Managing or optimizing the revenue a publisher gets from its inventory—usually by varying the price, underlying audience data, and sales approach.
For instance, a publisher could sell its premium placements directly but farm out excess inventory to ad networks, using yield optimization algorithms.

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