Last Thursday I attended a tweet chat on the #MarTechChat “channel”, on the topic of Dirty Data. Quite a few nuggets of wisdom were shared, and I collected some of ’em here, because I’m such a good person. Also to get the image of Jennifer Grey and Patrick Swayze out of my mind’s eye and plant it in yours.
Now, in case you’re not familiar with the concept of a ‘tweet chat’, it’s an epilepsy-inducing form of online engagement in real-time, where you follow a flood of posts submitted by people with agendas, all tagged with a pre-agreed hashtag. The host of the tweet chat, likely with the help of a lot of Ritalin, guides the discussion by posting questions and tagging them with the prefix Q1, Q2, etc. Then everybody attempts to answer using the prefix A1, A2 etc. It’s all lots of fun and very educating, but only if you have good people like me who are willing, after the fact, to collect the best tidbits of 140-character wisdom and share it in a friendlier, far less chaotic format, like here.
Anyway, host David Crane from Integrate kicked things off by asking:
Q1: What are the biggest challenges to ensuring only accurate and complete data is injected into marketing and sales systems? #MarTechChat
— David Crane (@davidfcrane) February 19, 2015
Below are some of the more notable comments made in response.
Stephanie Best: “A1: Culture. Many marketers just don’t see data quality as their issue. It’s not just an IT issue.”
Sammeer Kahn’s response particularly resonated with me:
Followup A3: From my experience 50% of the leads bought from third party is a complete was of marketing dollars. #martechchat
— Sameer Khan (@SameerKhan) February 19, 2015
//platform.twitter.com/widgets.jsMy two cents on the matter: it’s a matter of education. The more people in the organization are aware of the implications of bad data, the more involved they will be in preventing it.
Next question was: “What are some common repercussions of bad prospect data quality creating dirty data that you’ve seen?” To which Jonathan Burg responded: “A2: [it[ inhibits being able to personalize and drive engagement”. Matt Heinz elaborated: “A2: The less you personalize & customize the message, the less your prospect will be listening”. Stephanie Best’s point was especially astute:
A2: Dirty data doesn’t just affect the now. It affects the analysis of what is working/not. So you’ll be making decisions for later too.
— Data Ready Marketer (@StephanieABest) February 19, 2015
My view is similar: bad data is an insight-killer. It distorts decision making processes, damages attempts at relevancy, and is overall a terrible bummer and should be avoided like the plague.
Later on, Craig Rosenberg, aka the funnelholic, made the following observation:
It’s funny to even talk about problem in b2b considering our relatively low volume. b2c guys laughing hysterically at this #martechchat
— Craig Rosenberg (@funnelholic) February 19, 2015
To which I fully agreed. Matt Heinz responded thoughtfully though: “maybe but our stakes in B2B are higher. Much more $$ at stake selling 6-7 figure deals vs. SlapChops & mattresses”. Craig’s point, as he then made clear, was that B2B should learn from B2C and not live under the Hubristic assumption that it’s a unique problem set. I think there’s a deeper point to develop here, as the comparison may sound hollow if you’ve only done B2B and not B2C or vice versa. Another post maybe.
Finally, several blaming fingers were pointed at B2B marketing automation systems, deemed as sorely lacking in the clean data department. Jonathan Burg noted thus:
— Jonathan Burg (@Jonmburg) February 19, 2015
//platform.twitter.com/widgets.jsI also found this observation by Matt on point:
In conclusion, here are my summary thoughts on the issue of dirty data:
- There are many sharp minds out there dealing with the pain of dirty data. If you’re a B2B marketer, don’t assume you’re the first to deal with this. If you know someone who’s a B2C marketer, pick their brains.
- In my experience, bad B2B data originates from multiple sources, but at the core of it there’s either lack of standardization, inability to enforce one even if it exists, or too many rogue systems / marketers in the game.
- Manual enrichment should be employed way more than it is, especially where incoming lead volumes are modest.
- I think awareness to the problem is a pre-requisite to solving it, and for marketers willing to tackle it the fruits are sweet and plentiful.
And here’s what I learned about tweet chats:
- It’s hard to follow a tweet chat in real time.
- Everybody in such chats has an agenda. Mea Culpa.
- If the topic is wide enough and the participants are interesting, there’s good exposure value in a tweet chat. Per data shared in the session, the hashtag #MarTechChat generated 130,000+ reach & 3,059,256 impressions during the session. Not too shabby.