For me, trade shows and data go hand in hand, which isn’t an unusual way of thinking I suppose because, I work in a data management business. You on the other hand probably don’t work in data management, so please bear with me…
It’s universally agreed, that data is at the heart of every organisation and should be your prized asset… but only if it is receiving the required levels of care and attention.
In this article, I’m going to concentrate on some of the key check-points for building and/or acquiring your prospect (marketing/sales leads) data, but before you do, I would highly recommend that you first carry out an internal data audit and attempt to define your overall data aims.
Why you need a solid strategy
Having a solid data strategy will enable your organisation to realise its marketing and overall business goals through an action plan of achievable objectives.
Whether it’s for targeted marketing campaigns, lead generation or driving sales revenues, a well-managed prospect and customer database, is the essential component you will need.
Properly maintained, it can provide you with high quality, easily accessible data and, dramatically increase return on investment:
- Reducing costs (time spent trawling through aged and duplicated data silos and data records dotted around the organisation)
- Improving response (higher delivery and open/read rates by a precisely targeted audience)
- Driving up your audience or client quality
Data In Building Blocks
I would recommend you think of your database as a building block of modules that is glued together by common stored information i.e. it should be relational and not held as flat files such as excel worksheets.
You may well already use a data management system or CRM* tool, if so you are probably familiar with the types of modules I refer to e.g.
- Parent Accounts (companies)
- Accounts (companies)
- Contacts (customers/users)
- Leads (prospects)
- Events and/or other Products E.g. Newsletters, Magazines
In most CRM applications, the overall process is a sales pipeline to help push along unqualified leads into becoming qualified and then ‘customers’. This generally means that once a lead is qualified or becomes a customer, it will be converted in to a ‘Contact’, which in turn is linked to an ‘Account’.
*The term CRM has many meanings to different people. Very few businesses fully utilise a CRM process, but instead refer to ‘CRM’ as the system that hosts their prospect and customer data.
1. Consistency with data entry is King
– uniform formatting helps organise, segment and analyse data
– standardising names reduces duplication
– casing creates user friendly, user ready data
There are far too many granular sub-headings to document here, but as an example, the type of decisions you need to think of might include: will you be calling leads/contacts from your data regularly? If so, will you be using automated calling? If so, do telephone numbers need to be keyed or formatted in a standard structure?
Read this associated article for more on trade shows and data
2. Determine the sectors, sub-sectors and companies you wish to target:
– this can evolve as you add more sectors over time
3. Create a classification for the sectors and companies:
– aid quick and easy data selection and analysis
– analyse and review universe/sector penetration
A Simple Account Classification Example
Account Classification
- Sector
- Company type
- Company sub-type
- Revenue
- Employees
- Top 100
You can choose to use or adapt existing classification options such as SIC codes, NAICS or LinkedIn’s relatively new list, or create a new one to fit your specific requirements.
4. Similarly create a classification for Leads & Contacts:
– there are 1000’s of Job Titles, they need to be rationalised
– seniority is often good for determining decision making
– good classification helps you to segment and target and cut out ‘Spray & Pray’ marketing efforts
Contact/Lead Classification
- Job function
- Seniority
Job Functions should be generic and descriptive so they help consolidate all relevant job titles e.g. Marketing, Finance, Operations
Seniority can be grouped as for example: c-level, senior (to include heads, vp’s, directors), middle (managers), junior.
5. Determine the Data Fields your Database will require and split accordingly for the different modules:
– too much data can swamp the process; be selective and clear on what information is essential (you can always append more later)
– data often rests in databases unused and decaying because it’s irrelevant, its structure isn’t user-friendly or vital fields weren’t captured/populated
– ‘Free Text Fields’ can be the Devil’s only friend, spouting uncontrollably. They are best used only for personal notes such as conversation histories, or precise fields such as names and addresses
– often these are organisation specific, dependent upon personal needs, but examples of typical (basic) B2B Database Field Structures might be as follows:
Accounts (Companies)
Field Name Description Data Type
Account name Company name Text box
Account owner Internal responsibility Text box
Website URL
Parent account Parent company Text box
Employees Number of employees Numeric
Industry sector Pick list
Account sub-type Company type Pick list
Account type
Account ID Unique ID Numeric
Phone Company phone Text box
Industry Code e.g. SIC/NAICS Text box
Created By Date/Time
Modified By Last modified by Date/Time
Revenue Annual turnover Numeric
Billing Address Information
Street Text box
City Text box
County/State Text box
Post/Zip Code Text box
Country Text box
Shipping Address Information
Street Text box
City Text box
County/State Text box
Post/Zip Code Text box
Country Text box
Description Company information Free text
Leads & Contacts Data
Record owner Internal responsibility Text box
Contact ID Unique ID
Salutation Drop-down list
First name Text box
Last name Text box
Account name Company name Text box
Account ID Numeric
Source Where lead came from Pick list
Industry sector Pick list
Revenue Annual turnover Currency
Phone Contact phone Text box
Mobile Contact mobile Text box
Email Email address
Secondary email Email address
LinkedIn ID Text box
Twitter ID Text box
Website URL
Lead status Sales pipeline Drop-down list
Employees Number of employees Numeric
Opt-out prevent emails/calls Drop-down list
Opt-out 3rd party prevent calls & emails from your company Drop-down list
Created by Name of original creator Date/time
Modified by Name of last modified by Date/time
Shipping Address Details
Street Text box
City Text box
County/State Text box
Post/Zip Code Text box
Country Text box
About Personal information Text box
6. Never populate a field with anything other than what is was designed for
– so often databases are littered with homeless entries e.g. multiple emails or phone numbers in one field, notes added inappropriately
– always consider how the data will be used, you don’t want to have to tidy it every time it’s worked with
Where and how best to build or acquire your data?
There are probably four main options for you to consider here:
- Research and build your data in-house
- Inbound & Outbound Lead Generation e.g. capturing details via SEO, Marketing Automation, Landing Pages, White Papers, Surveys, Events etc.
- Purchase your data from B2B list-sellers
- Engage with a data management company that will research and build your data tailored to your specific instructions
Research and build you data in-house
If you have the necessary resource and skills, this should ensure high quality data is built. However, costs will likely be prohibitive.
To research 1,000 contacts will on average take approximately 170 hours, this is without necessary validation and quality checking. This represents over 4 weeks’ work for one person.
Inbound & Outbound Lead Generation
These methods should always form part of your data marketing strategy, but as good as they are (if conducted effectively), they are not as controllable as directly targeting and researching the business data you need.
For example, if you are targeting 1000 identified organisations to connect with specific people (job functions) at each, relying on these techniques will return very low results in the time-frame you will be working to. Put simply, it’s too hit and miss to base your data building aims on.
Purchase your data from B2B list-sellers
I think we probably all receive a plethora of emails each month offering us B2B lists, covering just about every sector imaginable! I’m also sure, most of us that operate within the Exhibition sector have had our fingers burnt by falling for the “If it seems too good to be true, it probably is” scenario.
The data most of these companies try to sell is at best low quality, it’s generally inaccurate, aged and most definitely (despite what they offer) not ‘opted-in’. It’s unlikely to have been screened against the Corporate Telephone Preference Service (CTPS) and if you use it for email marketing, you risk being black-listed as a spammer.
There are some trusted sellers, however, it’s always worth remembering that this data is being constantly re-sold to multiple recipients and is therefore more likely to be weary and exhausted.
Read this white paper for more exhibiting know-how
Engage with a data management (data research) company that will research and build your data tailored to your specific instructions
This, is the most effective and cost efficient method for acquiring your data. For all intents and purposes it is the same as researching and building your data in-house, except you are significantly reducing your costs and outsourcing the function to a team of experts that specialise in this service. All data researched is bespoke, it’s validated, quality checked and delivered in the exact format you determine, ready to upload straight in to your database.
You will also be able to establish a longer-term relationship with this partner and they will get to understand your data, your methods, your pain points. They can also support you with on-going data refreshing and replenishing because…
Whichever method you choose to build your B2B database, it’s worth noting some recently published statistics from Dun and Bradstreet’s 2017 B2B Marketing Data Report which stated, in the next 60 minutes…
- 271 businesses will move
- 1274 business telephone numbers will change or be disconnected
- 673 new businesses will open
- 12 will file for bankruptcy
- 767 CEO or owner changes will occur
- 8 companies will change their names.
So once your commitment is made to building a B2B database, you’ll also need to pledge considerable support to maintain what is a dynamic entity or your hard work and investment will unfortunately, quickly dissipate.
Next, it’s time to consider your Data Governance plans as well as the upcoming General Data Protection Regulation (GDPR), the new data protection legislation effective from 25th May 2018. But I’ll save that for another time. And who said data was boring!
Take action now, starting with that internal data audit. Then define your data strategy for the year ahead.
