We have been in organizations that have tried to use temps for sales data cleansing, and now have clients that do this. We know why you do it, and what you seek to achieve. But often we see this endeavor is not done well and as a result, doesn’t get you where you want to go. We offer database and sales analytics software and services. Temp cleaning is not what we offer. We do clean customer data not as a stand-alone service, but to add more value so that our predictive models are more accurate and actionable. We use structured cleansing and matching processes, B2B databases, rigorous profiling and analytical validation procedures. But here we’ll share our observations and tips about using temps for your benefit. This is because we are passionate about data, and have seen many instances where data cleansing was not done right, and later we had to work harder to fix it. We sincerely hope you find these tips valuable. IT, Sales and Marketing should inform each other before data cleansing starts. Just like you wouldn’t dig a trench in your yard without calling Julie – we hope! – the group that initiates this activity must be transparent and inclusive of …Read More
Data.Dump
Think of the times in life when you are barraged with a tidal wave of information, but all you really want to know is, “what do I really need to know?” That inch-thick stack of mortgage paperwork. Credit card agreements. Mobile phone instruction booklets. Automobile owner manuals. Insurance policies. Now let’s picture the documents that tell you only what you need to know. Recipes, for instance. They tell you: Get these specific things out of the cupboard or fridge … if you don’t have some items, buy them … and this is how much you need … now do these actions in this order. Recipes walk you through only the actions needed to get the desired result. Recipes do not tell us all information there is to know about cooking and baking and the foods we’re making. There is a reason why measurements should be precise when baking. There is a science to proper substitutions. There is a method behind why some foods are ideal paired together and others should never touch each other on the same plate. But a recipe doesn’t get into all that. If you want more information, there are plenty of books and Internet sites where you can learn. CRM …Read More
Buying prospect data: Why it may cost you 125% more than you think
Sourcing new outbound leads is a never-ending endeavor for sales and marketing. Prophesies of cold calling being dead have not come true if only for the simple reason that prospecting through all channels must be on the table to fuel the engine of sales growth. Companies typically procure lead data from four main types of leads: Internally-generated leads: Referrals, word of mouth, events, etc. Intelligence-based leads: Newsfeeds, industry alerts, personnel changes, etc. InsideView is one good example of this, but we believe LinkedIn also fits this mold (the evolution of this is exciting) Special or vertical lists: Trade associations, commerce groups, organizations operating with a geographic charter Compiled lists: The likes of D&B and InfoGroup, including credit files But as any sales or marketing manager knows, simply dumping more records on a sales rep is a thing of the past. Lead nurturing and scoring are the norm, wherein prospects are nurtured until they raise their hands as hot leads, and are then forwarded to sales. In addition, predictive modeling that identifies the most likely prospects based on the “ideal customer” profile must be part of the mix. It’s clear that the prospects at the top of the funnel – the ones you might pay for – are not sales ready. Further criteria and …Read More
Top CRM Trends to Watch in 2012
Our CRM trends to watch in 2011 were among the most-read words here, all year. Now let’s look forward to what’s in store for sales and marketing data in 2012 … FUSION OF SFA WITH EMA = TRUE CRM: With continuing innovation, sales force automation systems (SFA) have been transformed into a sales rep’s best friend, as discussed in an insightful blog post at Software Advice: easier implementation, data accessibility and now the benefits of analytics and marketing automation are aiding the success of sales teams using these systems. The success of CRM and Marketing Automation is no secret. More B2B organizations will take advantage of this profitable alliance to create a true lead generation life cycle platform, so that the handoffs throughout the prospect -> lead -> nurture -> sale pipeline will become more seamless and accountable. To accomplish this, data, analytics and best practices will play an integral part in relevant communication. (Also see our slide presentation, “What CRM was supposed to be.”) MORE PRODUCTIVE CUSTOMER RELATIONSHIPS: The customer value equation will go further so companies and sales teams can generate more revenue and profit from existing customers. This means examining every aspect of customer value, determining where it will come from and coaching/training to empower sales teams with …Read More
Spring Cleaning: Data hygiene tips that keep your sales data always ready for analysis
Predictive analytics needs a foundation of clean data. Here are top tips from our most recent lead gen implementation on Salesforce.com. You can use these immediately in any environment: Address standardization and change of address. Typically up to 30% of records lack complete address information. This affects both deliverability and duplicate search. If you have not done so in 3 years, run a Change of Address (NCOA) process to get your customer’s new addresses. Stay up to date on your customers because 10% of businesses move each year. When you receive a street address change, but it’s a PO Box in the same city, retain both — one for mailing and one for secondary validation. Dupes are the silent killer. Because a single comprehensive definition does not fit all, de-dupe the files using a variety of match logic. You can try a loose match logic (a few criteria, gives more duplicates) or tight match logic (more criteria, resulting in fewer duplicates). Take address elements into account, but use transactional information to determine which record to keep or drop. For example, between duplicates you might want to merge a record with multiple contacts into a record with the largest sales amount or the record with the longest …Read More