These months are in general a yearly peak for conferences, written content and webinars from solution and service providers in the Master Data Management (MDM), Product Information Management (PIM) and Data Quality Management (DQM) space. With the covid-19 crises conferences are postponed and therefore the content providers are now ramping up the online channel.
As one who would like to read, listen to and/or watch relevant content, it is hard to follow the stream of content being pushed from the individual providers every day.
The Resource List on this site is a compilation of white papers, ebooks, reports, podcasts, webinars and other content from potentially all the registered tool vendors and service providers on The Solution List and coming service list. The Resource List is divided into sections of topics. Here you can get a quick overview of the content available within the themes that matters to you right now.
We all know the pain of receiving e-mails with offers that is totally beside what you need.
Now Twitter has joined this spamming habit, which is a bit surprising, because with all the talk about big data and what it can do for prospect and customer insight, you should think that Twitter knows something about you.
Well, apparently not.
I operate two Twitter accounts. One named @hlsdk used for my general interaction with the data management community and one named @ProductDataLake used for a start-up service called Product Data Lake.
For both accounts, I am flooded with e-mails from Twitter about increasing my Holiday sales by using their ad services.
My businesses is not Business-to-Consumer (B2C) being about selling stuff to consumers, where the coming season is a high peak in the Western World. My business is Business-to-Business (B2B) where the coming season when it comes to sales is a stand still in the Western World.
The title of this blog post is a Latin legal phrase meaning “false in one thing, false in everything”. It refers to a principle about regarding everything a witness says as not credible, if one thing said by the witness is proven not to be true. This has been a part of the plot in plenty of courtroom films and TV-shows.
This principle has meaning related to data quality too. An example from direct marketing will be a receiver of a direct mail saying: “If you can’t get my name right, how can I trust you in getting anything right during a purchase?”
An example from the multi-channel world, or should we say omni-channel today, would be a shopper saying: “If you say one thing about the product in the shop and another thing on the website, how can I trust any of your product information?” Falsehood in omni-channel so to speak.
Measuring the impact of such attitudes and thereby the Return on Investment (ROI) in data quality improvement based on this principle is very hard. We usually only have random anecdotal evidence about that this happens.
But, what we can say is: Don’t lie in court and don’t neglect your data quality. It will hurt your credibility and then in the end your creditworthiness.
The article is about the implications for marketing caused by the rise of social media which now finally seems to eliminate what we have known as business-to-business (B2B) and more or less merges B2B and business-to-consumer (B2C).
As discussed here on the blog several times starting way back in 2009 in the post Echoes in the Database a problem with B2B indeed is that while business transactions takes place between legal entities a lot of business processes are done between employees related to the selling and buying entities. You may call that employee-to-employee (E2E), people-to-people (P2P) or indeed human-to-human (H2H).
Related to databases, data quality and Master Data Management (MDM) this means we need real world alignment with two kinds of parties:
While B2B and B2C may melt together in the way we do messaging the distinction between B2B and B2C will be there in many other aspects. Even in social media we see it as for example two of the most used social networks being FaceBook and LinkedIn clearly belongs mainly to B2C and B2B respectively for marketing and social selling purposes.
In the post Last Time Right the bad consequences of not handling that one of your customers aren’t among us anymore was touched.
This sad event is a major trigger in party master data lifecycle management like The Relocation Event I described last week.
In the data quality realm handling so called deceased data has been much about suppression services in direct marketing. But as we develop more advanced master data services handling the many aspects of the deceased event turns up as an important capability.
Like with relocation you may learn about the sad event in several ways:
A message from relatives
Subscription to external reference data services, which will be different from country to country
Investigation upon returned mail via postal services
Apart from in Business-to-Consumer (B2C) activities the deceased event also has relevance in Business-to-Business (B2B) where we may call it the dissolved event.
One benefit of having a central master data management functionality is that every party role and related business processes can be notified about the status which may trigger a workflow.
An area where I have worked with handling this situation was in public transit where subscription services for public transport is cancelled when learning about a decease thus lifting some burden on relatives and also avoiding processes for paying back money in this situation.
Right now I’m working with data stewardship functionality in the instant Data Quality MDM Edition where the relocation event, the deceased event and other important events in party master data lifecycle management must be supported by functionality embracing external reference data and internal master data.
As told in the post Psychographic Data Quality marketers are moving from demographic marketing to psychographic marketing where a lot more data than before are used to getting the right message, to the right suspect at the right time. This affects the way we are working with data quality around customer master data and eventually how we do multi-domain master data management.
Using data for building psychographic profiles not only deals with lead generation. It’s usable throughout the whole customer master data life cycle by for example:
Finding the best suspects at the right moment
Keeping the prospects on the optimal track coordinated with the prospects need
Ensuring a well received customer experience and facilitating up-sell and cross-sell.
Making win-back possible
These opportunities apply to business-to-consumer (B2C) and business-to-business (B2B) as well.
Location master data management is essential in this quest as well, because we are not abandoning the basic demographic attributes in the physiographic world. We are building a deeper data universe on top of the traditional demographic (and firmographic) data. Having accurate location master data only helps here.
Mastering product master data is essential in the psychographic world too. This does not only apply to having your product hierarchies well manages for your own products, but will eventually also lead to a need for handling data on your competitors products and services in order to listen to social data streams.
Master Data Management (MDM) will extend to Social Master Data Management and must support wider exploitation of big data sources by being the hub for the psychographic customer profiles and the reference for descriptions of the product and service realm related to the psychographic attributes.
Also this year I visited the Technology for Marketing and Advertising event in London in order to take part in as many prize drawings as possible. And oh, also to catch up on new developments in applying data quality to marketing.
Translation Management and Social Intelligence
SDL has the slogan: Because Business is Global. I like it. Besides doing translation management SDL also excels in social intelligence. As discussed with the SDL representative on the booth a core competency in doing this is to link social data with master data entities, a subject I touched yesterday on Informatica Perspectives in the post called Social MDM and Future Competitive Analysis.
A proof of that it is a small world is that Informatica is a SDL reference customer for localization as told here.
Utilizing Location Data
Entergate, a survey tool specialist, focused on a new tool called pointSurvey. It’s so new I can’t find any links on their website. The concept is embedding maps into surveys that relate to location data. Using the tool respondents may point out places of interest or draw out routes.
Surely this is a better way to catch locations than typing in postal addresses.
“At BriteVerify, we take verification seriously – in fact, making sure that you receive the most accurate information possible is pretty much the only thing that matters to us. Well, that and pancakes. Mmmmm… pancakes.”
Somehow I missed the pancakes. But the eMail verification presented by BriteVerify was good.
Recently I stumbled upon a report called Future Identities in the UK. The purpose of the report is to provide the government in the UK insight into how identities of citizens will develop over the next 10 years. But the insight certainly also applies to how private companies will have to react to this development and certainly also not just in the UK.
The report talks about three different kinds of identities:
Applied to data quality and master data management I think these future kinds of identities will have these consequences:
Biometric identities relates to hard core identity resolution as in fighting terrorism, crime investigation and physical access control but is sometimes even used in simple commercial checks as told in the post Real World Identity. My guess is that we will see biometrics used more as a mean to have better data quality, but not considerable more due to return of investment also as examined in the post Citizen ID and Biometrics.
Biographical identities and the related attributes resembles what we often also calls demographic attributes used in handling data for direct marketing and other purposes of data management. Direct marketing may, as reported in the post Psychographic Data Quality, be in transition to go deeper into big data in order to be psychographic marketing.
Social identities is the new black. As discussed on this blog, latest in the post Defining Social MDM, my guess is that social data master management is going to be big and has to be partly interwoven with using traditional biographical attributes and even, like it or not, biometric attributes. The art of doing that in a proper way is going to be very exciting.
The article explains how new sources of available data makes it possible for marketers to get a much closer look at potential customers and thereby going from delivering a broad message to a huge crowd to delivering a very targeted message to a small group of people with a high probability of getting a response. In short: Marketers are going from demographic marketing to psychographic marketing.
I believe this is true and ongoing (as I have also been involved in such activities).
The data quality issues we have always known in direct marketing is surely very similar in the psychographic marketing which is going on in the social media realm and in connection with eBusiness.
In my eyes, the concept of a single customer view is also a key to getting success in psychographic marketing.
You are not delivering a targeted message if you are delivering two different messages to two user profiles belonging to the same real world individual.
Your message will be very frustrating if you treat someone as a prospect customer if that someone already is an existing customer perhaps in another channel.
The effectiveness of psychographic marketing depends on a match between the psychographic variables, the behavioral variables and the demographic variables. As seen in the example in the Mashable article a good old thing as geocoding will be needed here.
An exciting thing in the rise of psychographic marketing is that it will add to the trend in data quality technology where it’s much more than simple name and address cleansing and deduplication. Rich location data will despite the virtual playground be further important. The relations between customers and products as described in the post Customer Product Matrix Management will be further refined in psychographic marketing.