Getting Better Analytics And Insights From Your Collected Customer Data

Data collection and analytics are tightly coupled. The mistake we see made over and over again is that companies tend to focus their customer data collection efforts with a single objective (or a single program) in mind. This treats the data collected as a short-term objective, not as a long-term asset. Over time, this results in data islands that eventually “go dark” given that no one is managing customer data as part of an explicit long-term effort.

Have A Long-Term Data Strategy

When it comes to customer data, a long-term data collection strategy almost always proves critical for any advanced analytical work that leads to meaningful business outcomes that can optimize (i.e., simulation management, condition-based maintenance, predictive maintenance and digital twins). Trending analysis, predicting behavior and customer profiling all benefit from long-term data collection strategies. Companies that understand customers’ buying patterns over longer time frames stand to win key insights versus their competitors.

Customer data deserves a data-access-centric strategy to ensure that the data is treated as a reusable asset. This implies that the data should be available to the right people in the company when they need to repurpose it or mine it months or years later. If the data is not findable, threadable (tied to other data sets) or readily accessible, then it’s effectively dark, and its chances of being repurposed are low.

If you are storing your customer data like you store everything else, chances are much of the data you’ve collected from customers has already gone dark. The tendency is to focus on analytical outcomes without preparing the precondition required for the analytics to occur over a longer period of time. If a data strategy for customer information isn’t well-executed, then customer data will reflect the problem you already have in your data center — lots and lots of data sets that represent difficult-to-access data islands.

Thread Your Data

Sophisticated analytical efforts require advanced techniques such as data threading. Threading data across many silos of data is a challenging undertaking. Techniques deployed to achieve threading include (re)ingestion of data, aggregation, parsing, meta data enrichment and indexing. Data is often so extremely siloed that the most efficient first step is simply discovering data islands and recollecting them into an architecture that allows for advanced analytics. The good news is that data capture and storage technologies are relatively cheap, but finding data and then curating it properly does require significant investment.

Customer data needs to be curated and managed as an asset. As more data is collected, it needs to be aggregated with customer data collected during the previous year (or the last campaign, the last payables cycle, etc.).

For example, if a financial institution wants to understand if a customer is approaching a life-changing event such as marriage, having children or purchasing a home, then threading becomes important because it lets you piece together various customer data collection efforts into a single threaded digital dossier. The threaded customer digital dossier allows for different customer data (collected at different points in time) to be accessed for future analytics. It treats customer data as valuable, evergreen and interconnected. A data architecture that allows you to thread and incrementally expand the customer data set is an essential component to making more with your customer data. Advanced analytics, in turn, will allow you make better use of customer data that is properly curated through threading or other data access techniques.

Teamwork

Separating the customer data collection process from the data curation process from data analytics is not a recipe for success. Unfortunately, most companies treat these three activities independent of each other. As a result, customer data is underutilized, undervalued and is not curated as a long-term asset.

The best customer analytics happen when you intersect people who understand the customer data being collected with people who understand how to use and access the data over time. This means that customer data collection efforts need to be discussed in one room with data architecture folks, analytical/data science teams and traditional marketing/customer success teams, ensuring that all have an active voice at the table.

[“Source-forbes”]

Insights into atomic structure of next-generation superconductors

Insights into atomic structure of next-generation superconductors

Neutron diffraction at the Australian Centre for Neutron Scattering has clarified the absence of magnetic order and classified the superconductivity of a new next-generation of superconductors in a paper published in Europhysics Letters.

The iron-based nitride, ThFeAsN, which contains Th2N2 and FeAs2 layers, has been of considerable interest because unconventional superconductivity occurring at a temperature of 30 K. This material was of particular interest as the superconductivity was seen to arise without oxygen doping.

A large group of predominantly Chinese researchers, led by Prof Huiqian Luo from the Beijing National Laboratory for Condensed Matter Physics gathered diffraction measurements on the high intensity diffractometer WOMBAT, assisted by instrument scientists Dr Helen Maynard-Casely and Dr Guochu Deng based at the Australian Centre for Neutron Scattering. This enabled them to determine the crystal structure of the compound over a large temperature range.

In similar types of materials, the onset of a superconducting state is thought to be associated with magnetic ordering within the crystal structure. Earlier measurements had shown no magnetic ordering in the ThFeAsN material, and hence this neutron study was an opportunity to confirm this and search for other structural insights into the material’s properties.

The lack of magnetic order was confirmed because no difference was found between the data sets at 6 K and 40 K. All of the observed reflections could be could be identified as having arisen from the atomic structure from 6K up to 300K – no magnetic reflections were identified.

Diffraction patterns over the temperature range from 300 K to 6 K also indicated there was no structural phase transition from tetragonal to orthorhombic in the crystal lattice.

The investigators reported that the lattice parameters continuously increased with temperature due to thermal expansion and a weak distortion in the tetrahedron possibly took place at 160 K. Details from the structure point to this distortion coming from the FeAs2 layers.

The close relationship between local structure of the FeAs4 tetrahedron and the superconducting temperature, suggested TheFeAsN is in a nearly optimised superconducting state.

This is different to many other discovered superconducting materials, which require tweaks in their chemistry to produce the highest critical temperature.

The authors also surmised that the close distance of Fe-As would favour electron hopping, reducing electron correlations and orbital order, thereby providing a reasonable explanation for the absence of magnetic order, structural transition and resistivity anomaly.

Carrier density measurements indicated that ThFeAsN could already be doped by electrons, which are probably introduced by the N deficiency or O occupancy or the reduced valence of nitrogen. The self-doping effect could be responsible for the superconductivity and suppression of magnetic order.

 

[“Source-phys”]

Key Consumer Sector Insights

Market and consumer sector’s performance last week

The second quarter earnings season ended on a productive note. The S&P 500 Index (SPY) (SPX-INDEX) finished the week ending September 1 on a positive note with a 1.4% gain. Brown-Forman stock rose last week and benefited the consumer staples sector with its strong 1Q18 results. On the other hand, Campbell Soup stock (CPB) pulled down the staples sector. Its earnings and revenues missed its fiscal 4Q17 results. Overall, the S&P 500 Consumer Staples Index rose 0.51% last week.

Key Consumer Sector Insights for August 28–September 1, 2017

In the consumer discretionary sector, Best Buy (BBY), H&R Block (HRB), and Dollar General (DG) fell last week after their earnings results. However, automakers General Motors (GM) and Ford (F) rose. Their August sales results benefited the sector. The S&P 500 Consumer Discretionary Index rose 1.6% last week.

Other events last week that impacted the market included the US August jobs report on Friday. The United States Department of Labor said that the US economy added 156,000 jobs in August—lower than economists’ expectations of 180,000 jobs. The unemployment rate in the US rose to 4.4% from 4.3%. Average hourly wages rose 2.5% in the past 12 months. The disappointing jobs report might reduce the chances of another Fed rate hike this year. The jobs report had a subdued impact on the S&P 500 because automakers’ stock rose.

Consumer ETFs were productive last week. The Consumer Discretionary Select Sector SPDR Fund (XLY) rose 1.6% on a weekly basis—the highest among consumer ETFs. The SPDR S&P Retail ETF (XRT) rose 1.0% and the Consumer Staples Select Sector SPDR ETF (XLP) rose 0.55% last week.

Consumer Sector Overview: August 28–September 1, 2017 PART 2 OF 6

Analyzing the Consumer Sector’s Performance Last Week

Index performance last week

As of September 1, the S&P 500 Index (10.6%) (SPY) (SPX-Index) has outperformed the S&P 500 Consumer Discretionary Index (10.4%) (XLY) and the S&P 500 Consumer Staples Index (6.1%) (XLP) on a YTD (year-to-date) basis.

Analyzing the Consumer Sector’s Performance Last Week

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Key updates

On September 1, General Motors (GM) released its August sales report. In August, US retail sales recorded 275,552 vehicles—7.5% higher YoY (year-over-year). The company’s commercial sales have risen 19% YoY. General Motors gained domestic commercial market share for 13 consecutive months. Its commercial market share was driven by strong crossover sales at all four of the company’s brands. General Motors stock rose ~5.0% last week.

On September 1, Ford (F) released its sales results for August. The company’s overall sales fell 2.1% to 209,897 vehicles in August. It was mainly impacted by lower fleet sales, which fell 0.2%. Ford’s retail sales for August fell 2.7% to 164,067 vehicles. Its stock rose ~5.0% in the week ending September 1.

L Brands (LB) released its August 2017 sales report on August 31. Its net sales for the four weeks ending August 26, 2017, fell 1.0% YoY to $842.1 million. Its comparable sales also fell 4.0% in August. The company’s exit from the swim and apparel categories impacted comparable store sales for Victoria’s Secret by three percentage points and overall sales by two percentage points. As of September 1, the stock rose 2.4% last week.

[“Source-Market Realist”]

 

E-Scan offers digital marketing insights

The Credit Union National Association recently released the 2017-2018 Environmental Scan. The E-Scan offers insights in 10 primary areas affecting credit unions, including lending, economics, technology and of course marketing. The E-Scan is a must-read for any credit union executive and is also an outstanding planning tool to use.

The marketing section is entitled “The Big Deal Behind Social Media.” It also mentions many of the other top marketing trends for credit unions, including disruptors, regulations, Generation Z, the evolution of marketing, highly personalized marketing, consumer preferences and the humanization of digital. But the bulk of the section centers around social media and engagement.

According to the E-Scan, there are five factors that come into play when brining engagement into your social media efforts:

(1)    Bring value first

As the E-Scan notes, “social media isn’t always about direct response…..once you’re identified as a serial promoter, people will shut you off and tune you out.” Look for ways to engage—not sell—on your social media platforms.

[“Source-cuinsight”]