14th Feb, 2020
Denave, Team, Designation
Data is the most critical asset for business success. While there’s nothing truer than this statement for all the businesses across the globe, it may still sound like a repetition to many. After all, ‘data is the new currency’, ‘data is an asset’ etc. chants have been doing rounds since more than a decade now.
Nevertheless, there’s a reason behind this repetition and that is, this truth is not being acted upon as it demands. The reasonings branch further into aspects like rapid pace of digital transformation, IOT data becoming a reality, growing volume and variety of data giving rise to a whole new breed of unstructured data and the list goes on.
Being the bedrock upon which rests the survival essentials (and growth catalysts) of any business, such as net new customer acquisition, exploration of whitespace, customer retention, global expansion of the brand et al, it becomes imperative for companies to begin treating B2B database as their most valuable resource.
Have a LOT of data but still struggling to make profits?
Having database is one thing and having quality-driven, intelligent and actionable data is another. Not having optimal amount of database is an obvious error and self-inflicted sabotage but many a times, even having sizeable database at disposal doesn’t do any good. Such scenarios of being unable to leverage the full benefit of customer data is a common concern amongst businesses, be it a start-up, small & medium organisation or big-league fishes. The simple reason behind this unexceptional distress amongst businesses is that they undermine the criticality of quality data. It is this attribute of data which brings it any worth.
This behaviour is at times intentional (owing to incorrect weighing of cost vs benefits) and at times unintentional (due to the lack of knowledge about the repercussions). However, the result is same in both the cases, i.e. hampered customer acquisition, low rate of renewals or customer retention, challenged upselling & cross-selling and even, failed attempts of geographical expansions.
Data quantity or quality – where to focus?
The answer is easy, when quantity is driven by quality, lead generation becomes easy. There’s a sea-difference between database and quality database. When basing their strategies on the prior without giving the quality aspect its due significance, companies put out themselves in vulnerable spot and are the first to succumb in the face of digital-led industrial transformation.
Misguided decision-making which follows inaccurate analytics resulting from corrupt data is a common phenomenon amongst companies who fail to recognise the impact of quality when it comes to data.
Reputational damage, missed opportunities and eventually, a substantial loss of revenue can be termed as the blanket impacts of bad data for companies.
To summarise it as succinctly as possible, bad data is bad for businesses.
On the other hand, good quality data has not one but many benefits which organisations stand to garner, such as:
Good quality data ensures targeted prospecting, aligned communications, boosted engagement and thus, an accelerated conversion of MQLs to SQLs.
Good quality data also allows the staff to be more productive since they’d be spending less time in validating the data or digging for the right information to fill-in the gaps.
A high-quality data translates into accurate analytics and which in turn propels better decision-making.
Better compliance management
Businesses also stand to save a significant sum of money since quality data adhering to geographical regulations mean a better compliance management and saving of hefty fines.
Data cleansing – What, why and how of it
Now that we understand the criticality of good quality data and the repercussions of dirty data, let’s look into the concept of data cleansing. Often also called as data scrubbing or appending, data cleansing is getting an accelerated traction these days owing to the enhanced focus on data regulations, customer information security protocols etc.
Many a times data cleansing is confused with data screening, however, they differ from each other in a major manner. While data screening involves catching of any erroneous data during the input stage, data cleansing pertains to fixing the errors in the data which has already been captured. Data hygiene management is another term which is used by many data practitioners when they refer to data cleansing.
Being the first step of effective data management, data cleansing includes tasks like completion, correction, deletion, filtration, deduplication etc. for ensuring the integrity and relevancy of customer database. Data cleansing not only transforms the bad data into its clean version but also brings consistency and uniformity in the picture in terms of data format.
Based on the nature of business and the frequency as well as the volume of data inflow, one can decide how often data cleansing is required.
When it comes to data cleansing methods, again, there is no standard procedure which can be applied to all the companies. The technique will entirely depend upon the type of data which is being used by a specific organisation and the ultimate purpose.
Here are some of the best practices to get started with cleansing of corrupt data on the right foot:
Evaluate your data
It is important that you understand your data in entirety before an external application begins its cleaning operations onto it. Assess the data via thorough data discovery sessions to see what all makes sense and what is completely redundant (so that you don’t waste time or resource on cleansing the now-irrelevant data). Identify the unique goals and objectives which you have before proceeding further.
Keep your safety net active
It is a good idea to keep a back up copy of all your data before you go into the action ground. This is just a contingency measure and will act as a fall-back option in case if something goes wrong even by chance. Also, keep a log of all changes to have a common progress sheet since a set of people might be involved in the process.
Do a researched investment
While investing into a database cleansing software (It is highly recommended since relying on manual resources for the process can be time-consuming and error-prone), thoroughly analyse all the features to ensure that it encompasses all your expectations.
If you still decide to do the chore in-house, it will be an intelligent decision to delegate the hard and repetitive job to automation by using various utility functions and tools which are specific to the platforms. Again, database experts would be the people who can guide and train your staff for using the right tools in the best manner (and therefore, outsourcing the entire activity might be a better idea since you will have the experts working for you).
Regularly assess the performance
Post the implementation of data cleansing system, it is advisable to do regular checks in terms of the quality score being delivered and other allied functions like the impact on decision-making, eventual time and monetary saving etc. to ensure if you’re on right track or any course-correction is required.
Trend of being data-rich but insight-poor
As per a new study published by Dun & Bradstreet and Forrester Research, nearly 50% of B2B marketers are relying mostly on intuition and experience rather than data.
Despite the fact that data formulates the foundation for all the key functions of any business, such as net new customer acquisition, retention of the old customers, demographic expansion of business outreach etc., there are many companies who are still not able to appreciate the actual value of B2B customer data they sit upon – whether it’s mined in-house or outsourced. Such companies can be termed as data-rich, but insight-poor. The arrangement in those organisations is such that the immense value of data sometime gets lost between the intricate operational layers of multiple systems etc.
These statistics reveal the true struggle going on in the industrial landscape where companies are still struggling to become data-driven:
- 80% of businesses “struggle to manage the volume, variety, and velocity of their data.
- Managing multiple CRM systems and data across technology silos is moderately to extremely challenging for 72% of B2B marketers.
- Only 41% of B2B marketers are satisfied with the analytics and reporting they receive from their current vendors
When we say data is the new oil, it can perhaps be likened to oil in literal terms. The way dug up oil has limited uses in its raw form, in the same way, data also requires conditioning and analytical treatment in order to reveal its true value in the form of intelligent B2B database.
With the latest advancement in the analytics domain, any business stands to get immensely benefitted if they are able to utilise the advanced analytics over their accrued data. Effective data collation combined with analytics has the power to steer the business in the direction of exponential growth.
Benefits of trading intuition for insight
While anticipation of customer needs (which is a primary ask of every business) and accordingly exhibiting proactivity can be the key value brought on by analytical tools, there are many other advantages which businesses stand to gain by choosing intelligent database instead of ‘just’ database, such as:
Accurate lead scoring
With compelling insights, you can score the leads in a more precise way, thus, ensuring the alignment of next steps in line with the weightage carried by each lead. In this way, lead prioritisation becomes easier than ever.
Gather net new leads
With the understanding of traits exhibited by high value leads (ranked through lead scoring and accurate customer profiling), similar attributes can be identified in newer audience and accordingly, targeted marketing engagement can be planned.
Better rate of customer acquisition
Having a more accurate buyer persona (data-driven profiles) and customer segmentation, automatically the rate of customer acquisition as well as renewals become better since you can align your marketing & sales strategy in line with the precise needs of the buyer.
Projecting customer lifetime value and profitability
Understanding the buying behaviour and projecting the future spends, buying frequency and level of loyalty allows better planning in terms of which customer/ customers require extra attention (and which don’t).
Efficient nurturing of pipeline
By understanding the blockers and bottlenecks in the sales funnel, it becomes easier to focus energies where they are required the most.
Personalised services and optimisation of customer experience
Getting real-time insights to fine-tune the communication for making it personalised is a major advantage offered by intelligent analytics. Also, leveraging its power for better operational management at the back-end ensures a superior customer experience at the front-end.
Along with the historic data (purchase patterns), with predictive analytics, it’s easier to gauge more accurate purchase intent and thus do more effective retargeting
Efficacy assessment of promotional activities
Evaluation of any activity is a must in order to plan forward-investments and data insights from any marketing campaign help in doing just that.
Why outsourcing your data needs can be the best decision for you?
When you outsource a task which acts as a fuel to propel your business in the direction of your vision, you not just save your money in the long-run but also the physical and mental bandwidth to focus on more important issues to accelerate your journey.
However, getting the right B2B database vendor is the key to get maximum value out of the outsourcing. Once you lay your hands on the right database company, it is like getting the last piece of the jigsaw puzzle right.
Here is a step by step guide to find your perfect match when it comes to getting a database vendor who provides not just quality database but also best-in-class actionable analytics:
Define your criteria
A quick checklist of specific aspects like your budget, definition of quality database in alignment with your business requirements etc. will help you in narrowing down your options.
Seek them where they ought to be present
Utilise internet search to find the better-known or ranked vendors. Also, attending industry events like seminars or trade shows allow for ample opportunities to meet a great variety of vendors in one place.
Involve your team
It is a good idea to ‘not’ take the decision of extending a proposal before discussing with your sales and marketing teams regarding their pain points or actual expectations. Inputs from the internal teams will help in outlining the spot-on proposal for the vendor.
Look for social proof
In this age of hyper-connectivity, don’t let go of the opportunity (as well as the need) to validate any vendor’s claim of perfection without checking out the testimonials from the industry peers or other industry recommendations.
Utilise the demo offers if available
It is always beneficial to get a chance to try before you buy. The same applies to database services as well. Check for the possibility of getting sample marketing list and do your set of due diligence in the form of test calls and mails to ensure you’re putting your money in a safe bet.
Whether doing cold calling or running strategic account-based marketing campaigns, quality B2B database is the starting point of your journey. In this age of information overflow, it is easy to become overwhelmed with the sheer velocity, variety and volume of data. The B2B marketers and business leaders who’d recognise the magnitude of the criticality which quality B2B contact data commands at this moment, will certainly be ahead in the competitive race.