Tag: DQ

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Dealing with Piranha infested rivers of data

Data is the piranha-infested river for successful marketing automation initiatives and this includes those that have things like ABM [1] in mind. Customer account data is messy at the best of times and requires both Marketing Automation and customer data knowledge, both of which are hard to find in a single resource or team.

Forrester’s research of “The US Marketing Technology And Services Outlook, 2017 To 2022” from 2017 suggested that US marketers would increase their investment in marketing technology by 27% reaching $122 billion spent on marketing tech by 2022, so we were all cautioned to not expect the pain and suffering of getting solutions in place, to let-up any time soon. Revenue in the IT Services market alone is projected to reach US$440.20bn in 2023 in the US according to Statista.

Online media spending in the US totaled $277.3 billion in 2022, up 13.5% from 2021, according to data from Winterberry Group (membership required).

The growth is below the 16.6% year-over-year growth predicted for 2022, indicating a deceleration in digital media spend, but online marketing spending accounted for over half (57.7%) of the $480.8 billion in total. In 2023, online marketing spending is forecast to grow by 10.8%, with market share predicted to rise to 60.3% of the total $509.2b expected to be spent.

The data problem has existed for as long as people have been collecting it and has become even more acute since the use of CRM became more commonplace. The promise of CRM like that of ERP is to hold all your data in an integrated and unified way so that marketing, sales, logistics, and accounting all have the same unified view. That single source of truth was hard to achieve in the first place and for many companies is still not really the way their data management approaches work.

With a large enterprise, there may be multiple systems of record, CRM, ERP, CDP, and then potentially multiples of each of those. Collecting customer data has created a mess of overlap and duplication because these platforms weren’t designed to function across multiple organizations or business units in some cases! Logistics for example probably don’t need access to the CDP.

Sales and marketing, customer service, support, warranties, assets, accounting, and others all have their own distinctive and siloed unique way of adding data into isolated systems, which complicates things even further. Combine that with the fact that many systems of a record actually source their data from a mess of data sources and sourcing channels with manual and automated connectivity, and you have a world that is inherently predisposed to data quality issues.

In reality, organizations need and want some central repository of critical customer data that they can consider as the entrenched source of truth so that they can galvanize all their other knowledge and insight around that single customer record. This in turn will help them provide an optimized experience and service levels to customers which in turn helps with retention and upsell.

What we have in the current CRM, ERP, and CDP offerings, is fractured and fragmented solutions which are mostly very good at solving the problems that were designed to solve but which don’t answer the other challenge of organizations, what are the key characteristics of my customer and is all the information that I have unified, proper and correct?

Only a customer master data management system can provide the essential data hub that can firewall, gate-keep, and appropriately distribute an authenticated and complete identity for the customer.

We believe the Pretectum CMDM is the ideal customer master data management solution for all shapes of business in all industries. Whether you have 1 system or 100 systems, Pretectum’s CMDM can support and speak to all of them. Whether you have 100 customers or millions, the Pretectum CMDM will help you curate them all and better still, provide them with their own self-service curation options that ensure you have the latest and best information.

With ABM, marketing resources are dedicated to a specific set of target accounts and the contacts within them. This highly targeted account-based strategy requires marketing and sales teams to align to deliver an on-point consistent and coherent message to the right person in a given account.

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Customer Master Data Management is strategic

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Putting a price on data is a tough task to perform if your business is not “in the business” of selling data. The real question though, is does your organization recognize its arguably most valuable data asset – customer master data, as a valuable resource? The true value of that data more than likely hides in how you use it.

Customer data holds enormous economic potential if managed well and appropriately leveraged. The challenge though is that many companies struggle with proper handling and syndication of their data. Further, they don’t think about their customer data strategically. They don’t take what they have and convert the data that is in hand, into actionable information. Worse, they may not be managing their customer data in any meaningful way, they may have data all over the place in systems, spreadsheets and even email.

By implementing some data management best practices around customer data, these same businesses could be thinking more strategically especially if they are ensuring that their data is accurate and aligned with their business objectives.

The practice of data governance has many facets. Master Data Management is just one of those and certainly, your master data management practice doesn’t have to cover all of these, particularly if the maturity of a given organization is not appropriate to an over-investment in policies and procedures, but there are some basics that you could and should consider.

Data governance includes all of the activities relating to the planning, implementation, development, and control of the information generated by an organization.

In other words, data governance is the development and realization of all the aspects that you might consider for data definition, creation, collection, storage, access, quality, change management and data distribution. Data governance also covers both the master and transactional data.

Pretectum sees data governance and the broader discipline of data management as covering many areas including data security, sharing, integration, architecture, MDM (Master Data Management), RDM (Reference Data Management), Insights and Intelligence, change management, storage, retention and retrieval

The best data is the data that is available and usable at exactly the right place and time, in the right format. While that is easily said, achieving this goal is a little more challenging depending on the maturity of your business practices, technology, the characteristics of the data itself and the nature of your industry.

There are key critical strategies and best practices that are generally accepted for improving the way companies manage their data, consider these aspects.

Forget the Rule of Thumb

We use the term frequently, and many businesses actually run their data governance program, if they have one, using the “Rule of Thumb”, but this approach is downright wrong.

At best, “Rule of thumb” is what you might consider an approximate method for data governance, sure, it is based on practical experience, but it is tribal in nature and really only as good as the individuals and the experience that they have with the maintenance of the program.

Having its roots in seventeenth-century trades where weights and measures were almost non-existent and certainly not measured and prescribed, quantities were measured by comparison to the width or length of some sort of loosely defined measure. A thumb, for example often being used as the baseline. These rough swags are fine when you don’t need more control and precision but unfortunately with the growing interest in compliance and meeting regulatory policy, managing data in a loose way is no longer acceptable.

Apart from any business rules you might have in place, there may be a raft of additional rules that are imposed by regulators specifically because of the nature of the data.

Having a robust approach to data governance provides some assurance that data meets the needs of the business and the legal obligations of the environment in which the business operates.

Data governance programs have several hurdles to overcome in order to be part of the DNA of the way the business views and deals with its data. There are cultural challenges, organizational politics and the simple mechanics of basic data control and management.

The technology aspects may be the least of your concerns if you have the right expectations defined in terms of requirements and the right level of complexity and flexibility in a given selected vendor.

The Pretectum CMDM affords you a number of different ways to meet your organizational objectives for Customer Master Data Management as part of a larger data governance program. Reach out today to learn more.

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Good customer analytics starts with good data

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The Importance of Comprehensive and Correct Customer Data

Consumer data helps companies a great deal to improve nearly every aspect of their business. With proper data analytics and a data-driven marketing approach, brands are able to gain actionable customer insights, generate quality leads and increase customer loyalty, among other things.

According to a survey done by Harvard Business Review, 58% of enterprises have experienced a hike in customer retention and loyalty by making the right use of customer analytics. 

Elevating the quality of your customer data can benefit your business in a number of ways and here are a few thoughts on aspects you might want to consider:

The enhanced customer experience (CX): There is evidence to suggest that businesses that are customer-centric tend to be way ahead of their competitors. To follow a customer-driven approach, you need access to comprehensive customer-specific data. The gathered and enhanced customer data can be useful in being able to understanding and predicting customer behaviour which in turn can be used to improve customer experience through customized offerings, messaging, interaction and services. Without the data, it is hard to provide anything more than a generic message or offer which may not resonate.

Precise targeting and lead generation accompanied with a lower CAC: Effective marketing can translate into a shorter sales cycle, greater sales volume, or appeal to a wider customer audience. For a marketing campaign to be effective though, it needs to have good data to support the estimation of the potential target market or market segment. Having good customer data opens up the opportunity to segment based on customer demographics, showing where the customers are, their age group, their gender, education, likely income, potential disposable income, and other critical traits that you might consider for targeting.

Drawing customers in for multiple engagements or appealing to new customers is made more likely with comprehensive and correct customer data that allow your business to focus on customer-characteristic-based marketing strategies to generate quality leads.

According to Thomas Griffin Co-Founder and President of OptinMonster in a piece on Forbes – customer acquisition cost (CAC) can be lowered if you have the right targeted message aimed at the right audience, whether it be PPC or contact-based marketing campaigns. To have that message, you need to know something about your audience, particularly if you’re running contact-based campaigns

Brand Improvement: Customer feedback and reviews form an important part of customer data but for this kind of data to be really useful, it needs to be tied to the best possible customer master data. To run effective customer review and survey data analytics you want to be able to paint a complete picture of respondents. Survey submissions that support uncovering the strengths and weaknesses of your brand and offerings can be effective in isolation by conveying a sense of general measures of customer satisfaction but they ultimately reduce their usefulness without reference to customer data.

Survey responses may impair your ability to derive maximum value from responses by being unable to tie them back to the respondent’s lifetime customer value. The CLV model informs you on whether the commenting customers are actually high-value customers or one-off customers who bought on a deal or opportunistically and that may never buy from you again.

Tools matter: we’ve talked about tools before, principally tools like your Customer Data Platform (CDP) and Customer Relationship Management (CRM) solution where you store large amounts of data and consumer profiles. You may even have an ERP (Enterprise Resource Planning) system or a CDM (Customer Data Management) platform. Your business may in fact have all of these., but the question of whether they are fit for purpose or suitable for all the jobs that your business needs to undertake needs to be carefully considered.

We’ve observed that there is a lot of enthusiasm about using AI for data collection accompanied by scraping tools and social media trawlers and transaction aggregators to increase the volume of data collected.  What we’ve also observed is that some of the fundamentals of knowing your customer remain missing or incomplete. This is partially due to poor data collection, collation, and assessment processes but it is also a function of the nature of the tools. Some tools are better suited to transaction processing, interaction or engagement, etc. Very few of the tools that we’ve mentioned, are suited to mastery of the digital customer and if they are, it is typically in the service of a specific application objective.

Customer data is presently experiencing a revolution in the business world. Data for every kind of business, from B2B sales and eCommerce brands to digital content creators, service and hospitality, healthcare and financial services, and a number of others too. All depend on gaining a source of appropriate and correct customer data to increase their leads, opportunities, and ultimately business., Knowing the audience, creating personalized marketing strategies, generating quality leads, and reaching a wider audience is the brass ring that leads to business success.

There is no exaggeration in saying that in today’s world of digital advancement, your company cannot survive without the best possible proper and relevant customer data. We believe you can achieve that with a Customer Master Data Management (CMDM) platform like that offered by Pretectum.

Contact us today for more information.